{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-09-23T00:17:47.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2026-09-23T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":44688,"title":"World Cup 2018 Prediction!","description":"Which team will be the winner?\r\n","description_html":"\u003cp\u003eWhich team will be the winner?\u003c/p\u003e","function_template":"function y = Worldcup2018winner()\r\n  y = \"????\"\r\nend","test_suite":"%%\r\nteams={'Russia','Saudi Arabia', 'Egypt', 'Uruguay', 'Portugal', 'Spain','Morocco','Iran',...\r\n    'France','Australia', 'Peru','Denmark', 'Brazil', 'Switzerland', 'Costa Rica', 'Serbia', ...\r\n    'Germany', 'Mexico', 'Sweden', 'STH Korea', 'Belgium', 'Panama', 'Tunisia', 'England' , ...\r\n    'Argentina','Iceland', 'Croatia', 'Nigeria', 'Poland', 'Senegal', 'Colombia', 'Japan'};\r\nd=false;\r\nfor i=1:numel(teams)\r\n    if strcmp(Worldcup2018winner(),teams{i})\r\n        d=true;\r\n        break;\r\n    end\r\nend\r\nassert(d)","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":218677,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":146,"test_suite_updated_at":"2018-06-15T17:39:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-06-15T17:38:14.000Z","updated_at":"2026-09-18T04:03:23.000Z","published_at":"2018-06-15T17:38:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml 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width=\"283.5\" height=\"20\" style=\"width: 283.5px; height: 20px;\"\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 94.4667px 8px; transform-origin: 94.4667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eGiven the input probabilities\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv 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width=\"224\" height=\"20\" style=\"width: 224px; height: 20px;\"\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function P_LS = verify_bayes_theorem(P_SL, P_L, P_S)\r\n  P_LS = P_SL;\r\nend","test_suite":"%%\r\nP_SL = 0.99;\r\nP_L  = 1/3;\r\nP_S  = 0.5;\r\nP_LS_correct = 0.66;\r\nP_LS = verify_bayes_theorem(P_SL,P_L,P_S);\r\nassert(abs(P_LS_correct-P_LS) \u003c eps)\r\n\r\n%%\r\nP_SL = 0.75;\r\nP_L  = 1/5;\r\nP_S  = 0.25;\r\nP_LS_correct = 0.6;\r\nP_LS = verify_bayes_theorem(P_SL,P_L,P_S);\r\nassert(abs(P_LS_correct-P_LS) \u003c eps)\r\n\r\n%% Test forbidden functions\r\nfiletext = fileread('verify_bayes_theorem.m');\r\nillegal = contains(filetext, 'regexp') || contains(filetext, 'str2num') || contains(filetext, 'assignin') || contains(filetext, 'echo')\r\nassert(~illegal);","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":149128,"edited_by":149128,"edited_at":"2025-07-10T07:02:07.000Z","deleted_by":null,"deleted_at":null,"solvers_count":46,"test_suite_updated_at":"2025-07-10T07:02:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2025-07-08T12:54:24.000Z","updated_at":"2026-09-14T06:34:16.000Z","published_at":"2025-07-08T13:17:57.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCompute the probability\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_{LS} = P(girl ~likes ~ you ~ | ~ she ~ smiled ~ at ~ you) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGiven the input probabilities\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_{SL} = P(she ~ smiles ~ at ~ you ~ | ~ she ~ likes ~ you)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_L = P(she ~likes ~ you) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_S = P(she ~ just ~ smiles ~ in ~ general) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44493,"title":"The great 82-year-old","description":"Let's answer the question below;\r\n\r\n'I am *x* years old and I have never written programs.\r\nIf I study from now, will I be able to develop programs?'\r\n\r\ninput *x* (years old) \u003e\u003e\u003e output 'Yes' or 'No'","description_html":"\u003cp\u003eLet's answer the question below;\u003c/p\u003e\u003cp\u003e'I am \u003cb\u003ex\u003c/b\u003e years old and I have never written programs.\r\nIf I study from now, will I be able to develop programs?'\u003c/p\u003e\u003cp\u003einput \u003cb\u003ex\u003c/b\u003e (years old) \u0026gt;\u0026gt;\u0026gt; output 'Yes' or 'No'\u003c/p\u003e","function_template":"function Answer = Age(x)\r\n  Answer = 'Yes';\r\nend","test_suite":"%%\r\nx = 20;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))\r\n%%\r\nx = 40;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))\r\n%% Great Ms Masako Wakamiya\r\nx = 82-1;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":137687,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":154,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2018-01-08T12:47:36.000Z","updated_at":"2026-08-20T13:44:45.000Z","published_at":"2018-01-08T12:58:55.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLet's answer the question below;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'I am\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e years old and I have never written programs. If I study from now, will I be able to develop programs?'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (years old) \u0026gt;\u0026gt;\u0026gt; output 'Yes' or 'No'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43747,"title":"Find the distance traveled by a car given velocity and time.","description":"A car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.","description_html":"\u003cp\u003eA car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.\u003c/p\u003e","function_template":"function y = distance(velocity,time)\r\n  D = time;\r\nend","test_suite":"%%\r\nvelocity = 10;\r\ntime = 60; \r\nD_correct = 600;\r\nassert(isequal(distance(velocity,time),D_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":100857,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":130,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-07T20:05:40.000Z","updated_at":"2026-02-10T21:28:41.000Z","published_at":"2016-12-07T20:05:40.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44413,"title":"determine amount cookies left","description":"started with 3 cookies and you never ate any how many are left","description_html":"\u003cp\u003estarted with 3 cookies and you never ate any how many are left\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 3;\r\ny_correct = 3;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":157993,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":133,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-11-24T06:51:36.000Z","updated_at":"2026-05-29T03:47:36.000Z","published_at":"2017-11-24T06:51:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003estarted with 3 cookies and you never ate any how many are left\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43557,"title":"Find hen's weight. ","description":"If hen weights x kilos on two legs, how much does it weights on one leg? Output the result.","description_html":"\u003cp\u003eIf hen weights x kilos on two legs, how much does it weights on one leg? Output the result.\u003c/p\u003e","function_template":"function y = Hen(x)\r\n  y = x-x+2*x+x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1-1+1-1-1+1+1-1+1-1+1-1+1;\r\nassert(isequal(Hen(x),y_correct))\r\n%%\r\nx = 2;\r\ny_correct = 1-1+1-1-1+1+1-1+1-1+1-1+1+1;\r\nassert(isequal(Hen(x),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":90467,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":138,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-15T10:07:55.000Z","updated_at":"2026-03-09T20:47:23.000Z","published_at":"2016-10-15T10:07:55.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf hen weights x kilos on two legs, how much does it weights on one leg? Output the result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":48015,"title":"Calculate the volume of the football","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63.9631px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.989px 31.9744px; transform-origin: 406.996px 31.9815px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9091px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.991px 10.4545px; text-align: left; transform-origin: 383.999px 10.4545px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the volume of a football given the ball radius r, using the formula below:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 34.0625px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.991px 17.0312px; text-align: left; transform-origin: 383.999px 17.0312px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg 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encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the volume of a football given the ball radius r, using the formula below:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eV_{sphere} = \\\\frac43 \\\\pi 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45-3;\r\nassert(isequal(TheAnswer(),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":14644,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":119,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-07T09:17:52.000Z","updated_at":"2026-02-12T18:40:12.000Z","published_at":"2016-10-07T09:17:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml 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?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":304,"title":"Bottles of beer","description":"Given an input number representing the number of bottles of beer on the wall, output how many are left if you take one down and pass it around.","description_html":"\u003cp\u003eGiven an input number representing the number of bottles of beer on the wall, output how many are left if you take one down and pass it around.\u003c/p\u003e","function_template":"function remaining = bottles_of_beer(on_the_wall)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 99;\r\ny_correct = 98;\r\nassert(isequal(bottles_of_beer(x),y_correct))\r\n\r\n%%\r\nx = 9;\r\ny_correct = 8;\r\nassert(isequal(bottles_of_beer(x),y_correct))\r\n\r\n%%\r\nx = 1;\r\ny_correct = 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type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44664,"title":"function to compute root mean square of first nn positive odd integers","description":"Write a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 84px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 42px; transform-origin: 407px 42px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 367px 8px; transform-origin: 367px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function orms = odd_rms(nn)\r\n  \r\nend","test_suite":"%%\r\nnn = 3;\r\norms_correct = 3.4156\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)\r\n\r\n%%\r\nnn = 10;\r\norms_correct = 11.5325\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)\r\n\r\n%%\r\nnn = 1;\r\norms_correct = 1\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":171559,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":59,"test_suite_updated_at":"2021-12-31T17:41:47.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-05-29T15:13:46.000Z","updated_at":"2026-05-30T00:36:27.000Z","published_at":"2018-05-29T15:13:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42632,"title":"Your favourite city!","description":"Type your favourite city.","description_html":"\u003cp\u003eType your favourite city.\u003c/p\u003e","function_template":"function y = favoriteCity()\r\n  y = '';\r\nend","test_suite":"%%\r\nassert(ischar(favoriteCity()))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":319,"test_suite_updated_at":"2015-09-23T05:22:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-09-23T05:19:30.000Z","updated_at":"2026-06-05T09:36:48.000Z","published_at":"2015-09-23T05:19:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eType your favourite city.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":748,"title":"Wrapping the Tower of Pisa","description":"The famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\r\n\r\nNote: inspired on problem 167","description_html":"\u003cp\u003eThe famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\u003c/p\u003e\u003cp\u003eNote: inspired on problem 167\u003c/p\u003e","function_template":"function y = paperneed(s,a)\r\n  y = s;\r\nend","test_suite":"%%\r\ns = pi;\r\na = pi^2;\r\ny_correct = 2*pi^4 + pi^3;\r\nassert(abs(paperneed(s,a)-y_correct)\u003c1e-12)\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":5,"created_by":4638,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":303,"test_suite_updated_at":"2012-06-06T20:53:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-05T11:41:10.000Z","updated_at":"2026-06-05T12:21:14.000Z","published_at":"2012-06-05T11:41:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: inspired on problem 167\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2053,"title":"Strange Number Algorithms","description":"Three integer numbers will be provided to you. Write a function to \r\n\r\n Step1: Multiply first number by 3.\r\n Step2: Add 6 with the getting result.\r\n Step3: divide it by 3.\r\n Step4: Subtract the first number.\r\n\r\n Step1: Double the second number.\r\n Step2: Add 9 with result.\r\n Step3: Subtract 3 with the result.\r\n Step4: Divide the result by 2.\r\n Step5: Subtract the result with the second number.\r\n\r\n Step1:Add 7 to the third number.\r\n Step2:Multiply the number with 2.\r\n Step3:Subtract 4 from the result.\r\n Step4:Divide the result by 2.\r\n Step5:Subtract the third number from the result.\r\n\r\nReturn a single row matrix with the three answers.\r\n\r\n","description_html":"\u003cp\u003eThree integer numbers will be provided to you. Write a function to\u003c/p\u003e\u003cpre\u003e Step1: Multiply first number by 3.\r\n Step2: Add 6 with the getting result.\r\n Step3: divide it by 3.\r\n Step4: Subtract the first number.\u003c/pre\u003e\u003cpre\u003e Step1: Double the second number.\r\n Step2: Add 9 with result.\r\n Step3: Subtract 3 with the result.\r\n Step4: Divide the result by 2.\r\n Step5: Subtract the result with the second number.\u003c/pre\u003e\u003cpre\u003e Step1:Add 7 to the third number.\r\n Step2:Multiply the number with 2.\r\n Step3:Subtract 4 from the result.\r\n Step4:Divide the result by 2.\r\n Step5:Subtract the third number from the result.\u003c/pre\u003e\u003cp\u003eReturn a single row matrix with the three answers.\u003c/p\u003e","function_template":"function amat = strange(n)\r\n  amat = n(1)-n(1)*3+6/3;\r\nend","test_suite":"%%\r\nn = [1 10 100];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [0 499 999];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [999 666 333];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [7 63 347];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":17471,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":101,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-12-15T06:55:46.000Z","updated_at":"2026-02-20T14:09:20.000Z","published_at":"2013-12-15T06:56:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThree integer numbers will be provided to you. Write a function to\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ Step1: Multiply first number by 3.\\n Step2: Add 6 with the getting result.\\n Step3: divide it by 3.\\n Step4: Subtract the first number.\\n\\n Step1: Double the second number.\\n Step2: Add 9 with result.\\n Step3: Subtract 3 with the result.\\n Step4: Divide the result by 2.\\n Step5: Subtract the result with the second number.\\n\\n Step1:Add 7 to the third number.\\n Step2:Multiply the number with 2.\\n Step3:Subtract 4 from the result.\\n Step4:Divide the result by 2.\\n Step5:Subtract the third number from the result.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn a single row matrix with the three answers.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44093,"title":"Determinants","description":"Given a square matrix(A), find the determinant(d).\r\n\r\nFor example:\r\n\r\nA = [1,3;4,5]\r\n\r\nd = 1*5-4*3 = -7","description_html":"\u003cp\u003eGiven a square matrix(A), find the determinant(d).\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cp\u003eA = [1,3;4,5]\u003c/p\u003e\u003cp\u003ed = 1*5-4*3 = -7\u003c/p\u003e","function_template":"function d = your_fcn_name(A)\r\n  d = A;\r\nend","test_suite":"%%\r\nA = [1,3;4,5];\r\nd_correct = -7;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [6,0,0,5;1,7,2,-5;2,0,0,0;8,3,1,8];\r\nd_correct = 10;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [1,0,4;2,3,2;0,5,-2];\r\nd_correct = 24;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [4,0,-7,3,-5;0,0,2,0,0;7,3,-6,4,-8;5,0,5,2,-3;0,0,9,-1,2];\r\nd_correct = 6;\r\nassert(isequal(your_fcn_name(A),d_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":126209,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":72,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-04-13T19:49:36.000Z","updated_at":"2026-03-16T09:24:14.000Z","published_at":"2017-04-13T19:52:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a square matrix(A), find the determinant(d).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA = [1,3;4,5]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ed = 1*5-4*3 = -7\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1667,"title":"What number has this problem?","description":"This problem is added because it is problem number *???* in the \"Community\" problems section.\r\n\r\n\u003chttp://www.mathworks.de/matlabcentral/cody/?sort=\u0026term=group%3ACommunity A lots of problems here!\u003e\r\n\r\n\r\nThank you, Community!\r\n\r\nand... \r\n\r\nThank you Matlab!!","description_html":"\u003cp\u003eThis problem is added because it is problem number \u003cb\u003e???\u003c/b\u003e in the \"Community\" problems section.\u003c/p\u003e\u003cp\u003e\u003ca href = \"http://www.mathworks.de/matlabcentral/cody/?sort=\u0026term=group%3ACommunity\"\u003eA lots of problems here!\u003c/a\u003e\u003c/p\u003e\u003cp\u003eThank you, Community!\u003c/p\u003e\u003cp\u003eand...\u003c/p\u003e\u003cp\u003eThank you Matlab!!\u003c/p\u003e","function_template":"function nr = celebrating_Problem()\r\n  nr = ???;\r\nend","test_suite":"%%\r\nweCelebrateProblemNumber = 1000;\r\nassert(isequal(celebrating_Problem(),weCelebrateProblemNumber))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":2,"created_by":3038,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":405,"test_suite_updated_at":"2013-06-20T22:47:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-20T22:38:15.000Z","updated_at":"2026-05-05T18:09:22.000Z","published_at":"2013-06-20T22:47:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis problem is added because it is problem number\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e???\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e in the \\\"Community\\\" problems section.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.de/matlabcentral/cody/?sort=\u0026amp;term=group%3ACommunity\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eA lots of problems here!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThank you, Community!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThank you Matlab!!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2416,"title":"Let's see how peculiar we can get","description":"The task is to multiply two numbers. But do it in the most peculiar possible way.","description_html":"\u003cp\u003eThe task is to multiply two numbers. But do it in the most peculiar possible way.\u003c/p\u003e","function_template":"function ans = multPec(x,y)\r\n  x*y;\r\nend","test_suite":"%%\r\nassert(isequal(multPec(2,3),6))\r\n\r\nassert(isequal(multPec(2,2),4))\r\n\r\nassert(isequal(multPec(10,-10),-100))\r\n\r\nassert(isequal(multPec(.2,-.3),-.06))\r\n\r\nassert(isequal(multPec(2i,1i),-2))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":199,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-07-13T17:25:26.000Z","updated_at":"2026-02-17T14:36:31.000Z","published_at":"2014-07-13T17:26:22.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe task is to multiply two numbers. But do it in the most peculiar possible way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44444,"title":"Problem 44444 !!!  free beer everyone","description":"just say hallelujah to solve this problem","description_html":"\u003cp\u003ejust say hallelujah to solve this problem\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = 'oups'%%%\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 'hallelujah';\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":111,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-08T13:35:52.000Z","updated_at":"2026-02-20T14:19:26.000Z","published_at":"2017-12-08T13:36:00.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ejust say hallelujah to solve this problem\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1230,"title":"Who is the smartest MATLAB programmer?","description":"Who is the smartest MATLAB programmer?\r\n\r\nExamples:\r\n\r\n  Input x = 'Is it Obama?'\r\n  Output = 'Me!'\r\n\r\n  Input x = 'Who ?'\r\n  Output = 'Me!'\r\n\r\nReturn 'Me!' to all inputs. (Note: this is only a joke!)","description_html":"\u003cp\u003eWho is the smartest MATLAB programmer?\u003c/p\u003e\u003cp\u003eExamples:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eInput x = 'Is it Obama?'\r\nOutput = 'Me!'\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eInput x = 'Who ?'\r\nOutput = 'Me!'\r\n\u003c/pre\u003e\u003cp\u003eReturn 'Me!' to all inputs. (Note: this is only a joke!)\u003c/p\u003e","function_template":"function y = smartest(x)\r\n  y = 'Not me!';\r\nend","test_suite":"%%\r\nx = 'I have been using MATLAB for 50 years!';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = 'I developed MATLAB!';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = '';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = 1;\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":3,"created_by":10338,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":793,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-30T01:41:14.000Z","updated_at":"2026-06-19T12:49:54.000Z","published_at":"2013-01-30T01:41:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWho is the smartest MATLAB programmer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Input x = 'Is it Obama?'\\nOutput = 'Me!'\\n\\nInput x = 'Who ?'\\nOutput = 'Me!']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn 'Me!' to all inputs. (Note: this is only a joke!)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43740,"title":"Create a New_Word","description":"The output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end. ","description_html":"\u003cp\u003eThe output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end.\u003c/p\u003e","function_template":"function y = New_Word(Old_Word)\r\n  y = Old_Word;\r\nend","test_suite":"%%\r\nOld_Word = 'Welcome';\r\ny_correct = 'meelcoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Pertinacious';\r\ny_correct = 'usertinacioy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Homogenous';\r\ny_correct = 'usomogenoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Homologous';\r\ny_correct = 'usomologoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Extemperaneous';\r\ny_correct = 'usxtemperaneoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Deterministic';\r\ny_correct = 'iceterministy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":100857,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2016-12-22T18:10:34.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-07T16:56:19.000Z","updated_at":"2026-05-29T02:43:19.000Z","published_at":"2016-12-07T16:56:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1437,"title":"Who has power to do everything in this world?","description":"There is only one person who is older than this universe. \r\nHe is Indian version of Chuck Norris.","description_html":"\u003cp\u003eThere is only one person who is older than this universe. \r\nHe is Indian version of Chuck Norris.\u003c/p\u003e","function_template":"function y = your_fcn_name\r\n  y;\r\nend","test_suite":"%%\r\nassert(isequal(your_fcn_name,'Rajnikanth'))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":3,"created_by":10792,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":491,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-19T19:24:35.000Z","updated_at":"2026-08-21T08:12:54.000Z","published_at":"2013-04-19T19:24:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is only one person who is older than this universe. He is Indian version of Chuck Norris.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44524,"title":"Perimeter of a quadrilateral","description":"There are four cars starting at a point.  The first car points north, the second one points east, the third one points south, and the last one points west.  Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west.  After t hours, the position of the cars can be viewed as a quadrilateral from space.  Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.","description_html":"\u003cp\u003eThere are four cars starting at a point.  The first car points north, the second one points east, the third one points south, and the last one points west.  Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west.  After t hours, the position of the cars can be viewed as a quadrilateral from space.  Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.\u003c/p\u003e","function_template":"function p = total_distance(n,e,s,w,t)\r\n  p = sqrt(n*e*s*t);\r\nend","test_suite":"%%\r\nn=10;\r\ne=10;\r\ns=10;\r\nw=10;\r\nt=2;\r\ny_correct=113.1371;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n%%\r\nn=15;\r\ne=7;\r\ns=3;\r\nw=15;\r\nt=1.5;\r\ny_correct=91.0185;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n%%\r\nn=11;\r\ne=21;\r\ns=31;\r\nw=41;\r\nt=1.7;\r\ny_correct=263.5003;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2018-02-16T18:58:53.000Z","updated_at":"2026-05-29T05:09:35.000Z","published_at":"2018-02-16T18:58:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are four cars starting at a point. The first car points north, the second one points east, the third one points south, and the last one points west. Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west. After t hours, the position of the cars can be viewed as a quadrilateral from space. Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1681,"title":"Do you like your boss?","description":"Do you like your boss?\r\nAnswer can be any string!\r\n\r\nFor example:\r\n\r\nBoss = 'Do you like your boss?';\r\n\r\nOutput = 'yes'\r\n\r\nor \r\n\r\nBoss = 'Do you like your boss?';\r\n\r\nOutput = 'Sometimes'\r\n\r\nor\r\n\r\nBoss = 'Do you like your boss?'\r\n\r\nOutput = 'No'\r\n\r\nBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\r\n","description_html":"\u003cp\u003eDo you like your boss?\r\nAnswer can be any string!\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?';\u003c/p\u003e\u003cp\u003eOutput = 'yes'\u003c/p\u003e\u003cp\u003eor\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?';\u003c/p\u003e\u003cp\u003eOutput = 'Sometimes'\u003c/p\u003e\u003cp\u003eor\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?'\u003c/p\u003e\u003cp\u003eOutput = 'No'\u003c/p\u003e\u003cp\u003eBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\u003c/p\u003e","function_template":"function Answer = YourBoss(Qustion)\r\n  Answer = 'So whats the answer???';\r\nend","test_suite":"%%\r\nx = 'Do you like your boss?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Does your boss smell funny?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Is your boss a man or a woman?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Is your boss mean or nice?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Do you see your boss often?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'If your boss were an animal, what type of animal would he or she be?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'On a scale from one to ten, where does your boss rank?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Maybe you are your own boss...';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Maybe your boss is standing behind you, with that glare on his face, tapping his foot with his arms folded...';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))","published":true,"deleted":false,"likes_count":5,"comments_count":2,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":647,"test_suite_updated_at":"2013-06-27T16:47:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-27T15:50:45.000Z","updated_at":"2026-08-14T23:15:04.000Z","published_at":"2013-06-27T16:00:56.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDo you like your boss? Answer can be any string!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?';\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?';\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'Sometimes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'No'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1384,"title":"Who invented zero?","description":"We know the importance zero in computer science, mathematics... but who invented zero?\r\n\r\nClue:\r\n\r\nHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.","description_html":"\u003cp\u003eWe know the importance zero in computer science, mathematics... but who invented zero?\u003c/p\u003e\u003cp\u003eClue:\u003c/p\u003e\u003cp\u003eHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.\u003c/p\u003e","function_template":"function y = zero()\r\n  y = 'zero';\r\nend","test_suite":"%%\r\nassert(isequal(zero(),'Aryabhata'))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":4,"created_by":6975,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":612,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-25T09:04:11.000Z","updated_at":"2026-08-15T02:34:27.000Z","published_at":"2013-03-25T09:04:11.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe know the importance zero in computer science, mathematics... but who invented zero?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eClue:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1188,"title":"The Answer to Life, the Universe, and Everything","description":"A variation of a previous Hitchhiker's Guide to the Galaxy problem.\r\n\r\n*Inputs:* Life, the Universe, and Everything\r\n\r\n*Output:* The Answer","description_html":"\u003cp\u003eA variation of a previous Hitchhiker's Guide to the Galaxy problem.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e Life, the Universe, and Everything\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e The Answer\u003c/p\u003e","function_template":"function answer = answer_to(life,universe,everything)\r\n  answer = [];\r\nend","test_suite":"%%\r\nanswer = 42;\r\nassert(isequal(answer_to('life'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('universe'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('everything'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('life','universe','everything'),answer))","published":true,"deleted":false,"likes_count":5,"comments_count":4,"created_by":1057,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":588,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-08T12:59:24.000Z","updated_at":"2026-08-28T11:45:28.000Z","published_at":"2013-01-08T12:59:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA variation of a previous Hitchhiker's Guide to the Galaxy problem.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Life, the Universe, and Everything\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e The Answer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":157,"title":"The Hitchhiker's Guide to MATLAB","description":"Output logical \"true\" if the input is the answer to life, the universe and everything. Otherwise, output logical \"false\".","description_html":"\u003cp\u003eOutput logical \"true\" if the input is the answer to life, the universe and everything. Otherwise, output logical \"false\".\u003c/p\u003e","function_template":"function y = zaphod(x)\r\n  y = false\r\nend","test_suite":"%%\r\nx = 41;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 42;\r\ny_correct = true;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 43;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 44;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 45;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 46;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 47;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 48;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 49;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 50;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))","published":true,"deleted":false,"likes_count":54,"comments_count":19,"created_by":39,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3426,"test_suite_updated_at":"2012-01-29T03:52:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-29T03:52:07.000Z","updated_at":"2026-08-19T06:23:07.000Z","published_at":"2012-01-29T03:53:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput logical \\\"true\\\" if the input is the answer to life, the universe and everything. Otherwise, output logical \\\"false\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":167,"title":"Pizza!","description":"Given a circular pizza with radius z and thickness a, return the pizza's volume. [ z is first input argument.]\r\nNon-scored bonus question: Why is the function interesting?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 102.5px 8px; transform-origin: 102.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a circular pizza with radius\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3.5px 8px; transform-origin: 3.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ez\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.5px 8px; transform-origin: 45.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and thickness\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ea\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 88px 8px; transform-origin: 88px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, return the pizza's volume. [\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3.5px 8px; transform-origin: 3.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ez\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 74px 8px; transform-origin: 74px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is first input argument.]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 190px 8px; transform-origin: 190px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNon-scored bonus question: Why is the function interesting?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = pizza(z,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('pizza.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'if') || contains(filetext, 'switch'); \r\nassert(~illegal)\r\n\r\n%%\r\nz = 1;\r\na = 1;\r\nv_correct = pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 2;\r\na = 1;\r\nv_correct = 4*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 1;\r\na = 2;\r\nv_correct = 2*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 2;\r\na = 2;\r\nv_correct = 8*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n","published":true,"deleted":false,"likes_count":377,"comments_count":316,"created_by":39,"edited_by":223089,"edited_at":"2022-12-19T07:41:42.000Z","deleted_by":null,"deleted_at":null,"solvers_count":24265,"test_suite_updated_at":"2022-12-19T07:41:42.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-29T16:17:01.000Z","updated_at":"2026-09-30T22:11:08.000Z","published_at":"2012-01-29T16:21:23.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a circular pizza with radius\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ez\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and thickness\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, return the pizza's volume. [\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ez\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is first input argument.]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNon-scored bonus question: Why is the function interesting?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":149,"title":"Is my wife right?","description":"Regardless of input, output the string 'yes'.","description_html":"\u003cp\u003eRegardless of input, output the string 'yes'.\u003c/p\u003e","function_template":"function out = wiferight(in)\r\n  out='no';\r\nend","test_suite":"%%\r\nx = 'But I''m actually right this time';\r\ny_correct = 'yes';\r\nassert(isequal(wiferight(x),y_correct))\r\n\r\n%%\r\nx = 'But you just said that 2+2=3';\r\ny_correct = 'yes';\r\nassert(isequal(wiferight(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":297,"comments_count":71,"created_by":39,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17468,"test_suite_updated_at":"2012-01-29T04:12:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-28T17:50:24.000Z","updated_at":"2026-09-27T17:44:28.000Z","published_at":"2012-01-29T04:12:44.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRegardless of input, output the string 'yes'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49962,"title":"When the sum of the squares is a cubic...","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 83.5px; transform-origin: 407px 83.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eConsider the following equality:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 65px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 32.5px; text-align: left; transform-origin: 384px 32.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"314\" height=\"59\" style=\"vertical-align: baseline;width: 314px;height: 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor a given value of n (i.e., num in the problem statement), determine the values of a's and b that satisfy the equality above. The answer should be put in a vector where the first \"num\" entries are the values of a's and the last entry is b. There is no unique answer to each of the problems; however, your answer will be checked against the requirement.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = square_cubic(num)\r\n  y = ones(num);\r\nend","test_suite":"%%\r\nnum=1;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=2;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=3;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=4;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=5;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=6;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":24,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-23T22:19:52.000Z","updated_at":"2026-05-30T22:18:56.000Z","published_at":"2021-01-23T22:20:27.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider the following equality:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"59\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"314\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor a given value of n (i.e., num in the problem statement), determine the values of a's and b that satisfy the equality above. 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Pillar","description":"Calculate the volume of a pillar with radius l and heigth ar.","description_html":"\u003cp\u003eCalculate the volume of a pillar with radius l and heigth ar.\u003c/p\u003e","function_template":"function y = Pillar_Size(l,ar)\r\n  y = x;\r\nend","test_suite":"%%\r\nl = 1;\r\nar = 2;\r\ny_correct = pi*2;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))\r\n\r\n%%\r\nl = 12;\r\nar = 25;\r\ny_correct = pi*3600;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))\r\n\r\n%%\r\nl = 6;\r\nar = 2;\r\ny_correct = pi*72;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))","published":true,"deleted":false,"likes_count":15,"comments_count":1,"created_by":99516,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2277,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-02-06T15:36:59.000Z","updated_at":"2026-09-30T22:25:20.000Z","published_at":"2017-02-06T15:36:59.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the volume of a pillar with radius l and heigth ar.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43571,"title":"How many hours are there in a day in Italy?","description":"Remember \"European Summer Time\"","description_html":"\u003cp\u003eRemember \"European Summer Time\"\u003c/p\u003e","function_template":"function HH = your_fcn_name(y,m,d)\r\n  HH = [y,m,d];\r\nend","test_suite":"%%\r\ny = 2016;\r\nm = 1;\r\nd = 1;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n%%\r\ny = 2016;\r\nm = 12;\r\nd = 31;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n%%\r\ny = 1965;\r\nm = 12;\r\nd = 7;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n\r\n\r\n%%\r\ny = 2016;\r\nm = 10;\r\nd = 30;\r\ny_correct = 25;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n%%\r\ny = 2016;\r\nm = 3;\r\nd = 27;\r\ny_correct = 23;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":14644,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-17T14:33:18.000Z","updated_at":"2026-05-29T01:44:44.000Z","published_at":"2016-10-17T14:36:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember \\\"European Summer Time\\\"\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1561,"title":"Reverse CHECKBOX MATRIX with 69","description":"Create a reverse checkbox matrix with '69'.   \r\nWhere the size is the input and output will be a square checkbox matrix. \r\n\r\nExample\r\n\r\nIf input is 4 then output will be \r\n\r\n    [ 0    69     0    69 \r\n     69     0    69     0 \r\n      0    69     0    69 \r\n     69     0    69     0]\r\n","description_html":"\u003cp\u003eCreate a reverse checkbox matrix with '69'.   \r\nWhere the size is the input and output will be a square checkbox matrix.\u003c/p\u003e\u003cp\u003eExample\u003c/p\u003e\u003cp\u003eIf input is 4 then output will be\u003c/p\u003e\u003cpre\u003e    [ 0    69     0    69 \r\n     69     0    69     0 \r\n      0    69     0    69 \r\n     69     0    69     0]\u003c/pre\u003e","function_template":"function y = ChecK69(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 3;\r\ny_correct = [0 69 0;69 0 69;0 69 0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 4;\r\ny_correct = [0    69     0    69;\r\n            69     0    69     0;\r\n             0    69     0    69;\r\n            69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 5;\r\ny_correct =[0    69     0    69     0;\r\n           69     0    69     0    69;\r\n            0    69     0    69     0;\r\n           69     0    69     0    69;\r\n            0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 6;\r\ny_correct =[0    69     0    69     0    69;\r\n           69     0    69     0    69     0;\r\n            0    69     0    69     0    69;\r\n           69     0    69     0    69     0;\r\n            0    69     0    69     0    69;\r\n           69     0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 8;\r\ny_correct =[0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":13514,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":86,"test_suite_updated_at":"2013-06-06T11:31:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-06T11:26:14.000Z","updated_at":"2026-03-05T16:34:45.000Z","published_at":"2013-06-06T11:26:18.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCreate a reverse checkbox matrix with '69'. Where the size is the input and output will be a square checkbox matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is 4 then output will be\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    [ 0    69     0    69 \\n     69     0    69     0 \\n      0    69     0    69 \\n     69     0    69     0]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1719,"title":"Dice face matrix!","description":"This is dice simulator, but instead of making a random die number, you will receive an \"pre-rolled\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\r\n\r\n  rollnum = 1;\r\n\r\nThen the output will be:\r\n\r\n  diceFace =\r\n  \r\n       0     0     0\r\n       0     1     0\r\n       0     0     0\r\n\r\nAnother example:\r\n\r\n  rollnum = 5;\r\n\r\nThen the output will be:\r\n\r\n  diceFace =\r\n  \r\n       1     0     1\r\n       0     1     0\r\n       1     0     1\r\nAnd so on for 1-6, well that is it!\r\nJust note the 1 and 0 are numbers not char's or strings...\r\nGood luck!","description_html":"\u003cp\u003eThis is dice simulator, but instead of making a random die number, you will receive an \"pre-rolled\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003erollnum = 1;\r\n\u003c/pre\u003e\u003cp\u003eThen the output will be:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ediceFace =\r\n\u003c/pre\u003e\u003cpre\u003e       0     0     0\r\n       0     1     0\r\n       0     0     0\u003c/pre\u003e\u003cp\u003eAnother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003erollnum = 5;\r\n\u003c/pre\u003e\u003cp\u003eThen the output will be:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ediceFace =\r\n\u003c/pre\u003e\u003cpre\u003e       1     0     1\r\n       0     1     0\r\n       1     0     1\r\nAnd so on for 1-6, well that is it!\r\nJust note the 1 and 0 are numbers not char's or strings...\r\nGood luck!\u003c/pre\u003e","function_template":"function diceFace = rollADie(rollnum)\r\n  diceFace = rollnum;\r\nend","test_suite":"%%\r\nrollnum = 1;\r\ndiceFace = [0 0 0; 0 1 0; 0 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 2;\r\ndiceFace = [0 0 1; 0 0 0; 1 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 3;\r\ndiceFace = [0 0 1; 0 1 0; 1 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 4;\r\ndiceFace = [1 0 1; 0 0 0; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 5;\r\ndiceFace = [1 0 1; 0 1 0; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 6;\r\ndiceFace = [1 0 1; 1 0 1; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":139,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":41,"created_at":"2013-07-16T15:48:23.000Z","updated_at":"2026-09-03T10:57:51.000Z","published_at":"2013-07-16T15:48:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is dice simulator, but instead of making a random die number, you will receive an \\\"pre-rolled\\\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[rollnum = 1;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen the output will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[diceFace =\\n\\n       0     0     0\\n       0     1     0\\n       0     0     0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnother example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[rollnum = 5;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen the output will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[diceFace =\\n\\n       1     0     1\\n       0     1     0\\n       1     0     1\\nAnd so on for 1-6, well that is it!\\nJust note the 1 and 0 are numbers not char's or strings...\\nGood luck!]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1712,"title":"NO _________ ALLOWED....","description":"So you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0.  For example:\r\n\r\n  Sentence = 'The birds in the field are eating bird seed';\r\n  Not_allowed = 'field'\r\n\r\nso the output will be, because field is found in the sentence:\r\n\r\n  Output = 1; \r\n\r\nAnother example:\r\n\r\n  Sentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\n  Not_allowed = 'oven'\r\n\r\nso the output will be, because oven is not found in the sentence:\r\n\r\n  Output = 0; \r\n\r\nThat is it!\r\n\r\nHave Fun!","description_html":"\u003cp\u003eSo you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0.  For example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eSentence = 'The birds in the field are eating bird seed';\r\nNot_allowed = 'field'\r\n\u003c/pre\u003e\u003cp\u003eso the output will be, because field is found in the sentence:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput = 1; \r\n\u003c/pre\u003e\u003cp\u003eAnother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eSentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\nNot_allowed = 'oven'\r\n\u003c/pre\u003e\u003cp\u003eso the output will be, because oven is not found in the sentence:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput = 0; \r\n\u003c/pre\u003e\u003cp\u003eThat is it!\u003c/p\u003e\u003cp\u003eHave Fun!\u003c/p\u003e","function_template":"function output = NotAllowed(Sentence, Not_allowed)\r\n  output = Not_allowed;\r\n  output = Sentence;\r\nend","test_suite":"%%\r\nSentence = 'The birds in the field are eating bird seed';\r\nNot_allowed = 'field'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\nNot_allowed = 'oven'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Oh where, oh where has my little dog gone?';\r\nNot_allowed = 'where'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Insanity: doing the same thing over and over again and expecting different results...';\r\nNot_allowed = 'Einstein'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Wheres the cream filling?';\r\nNot_allowed = 'cream'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'MATLAB is the coolest!';\r\nNot_allowed = 'MATLAB'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'No no, you got it all wrong!';\r\nNot_allowed = 'No'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'This planet, with all its appalling immensity, is to electric currents virtually no more than a small metal ball.';\r\nNot_allowed = 'Tesla'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":232,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-12T16:08:38.000Z","updated_at":"2026-05-12T20:49:10.000Z","published_at":"2013-07-12T16:08:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0. For example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Sentence = 'The birds in the field are eating bird seed';\\nNot_allowed = 'field']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the output will be, because field is found in the sentence:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Output = 1;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnother example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Sentence = 'If the sky is blue on earth, what is the sky color on mars?';\\nNot_allowed = 'oven']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the output will be, because oven is not found in the sentence:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Output = 0;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThat is it!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHave Fun!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42766,"title":"Is my wife really right?","description":"For every input, output the string 'yes' once.\r\nExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\r\nyes1 = 'yes'\r\nyes2 = 'yes'","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 111px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 55.5px; transform-origin: 407px 55.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 139px 8px; transform-origin: 139px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor every input, output the string 'yes' once.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 207px 8px; transform-origin: 207px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 37px 8px; transform-origin: 37px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyes1 = 'yes'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 37px 8px; transform-origin: 37px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyes2 = 'yes'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function yes = YesSheIs('?')\r\n  y = 'no';\r\nend","test_suite":"%%\r\nQuestion1 = 'Will you be ready soon?';\r\nQuestion2 = 'What is the meaning of life, universe and everything?';\r\nQuestion3 = 'Do you wan''t to go out today?';\r\nQuestion4 = 'Can you help me?';\r\ny_correct = ['yes', 'yes', 'yes', 'yes'];\r\n[yes1, yes2, yes3, yes4] = YesSheIs(Question1, Question2, Question3, Question4);\r\nassert(strcmp([yes1, yes2, yes3, yes4] ,y_correct))\r\n\r\n\r\n%% \r\nQuestion1 = 'Will you be ready soon?';\r\nQuestion2 = 'What is the meaning of life, universe and everything?';\r\nQuestion3 = 'Do you wan''t to go out today?';\r\nQuestion4 = 'Can you help me?';\r\ny_correct = ['yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes'];\r\n[yes1, yes2, yes3, yes4, yes5, yes6, yes7, yes8, yes9] = YesSheIs(Question1, Question2, Question3, Question4, Question1, Question2, Question3, Question4, Question3);\r\nassert(strcmp([yes1, yes2, yes3, yes4, yes5, yes6, yes7, yes8, yes9] , y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":68531,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":38,"test_suite_updated_at":"2021-09-05T10:31:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-03-07T17:01:12.000Z","updated_at":"2026-07-10T09:48:00.000Z","published_at":"2016-03-07T17:01:16.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor every input, output the string 'yes' once.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eyes1 = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eyes2 = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1630,"title":"~~~~~~~ WAVE ~~~~~~~~~","description":"|The WAVE generator|\r\n\r\nOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone. \r\n\r\n|For EXAMPLE|: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\r\n\r\n     1     1     1     1     1     1\r\n     1     2     2     2     2     2\r\n     1     2     3     3     3     3\r\n     1     2     3     4     4     4\r\n     1     2     3     4     5     5\r\n     1     2     3     4     5     6","description_html":"\u003cp\u003e\u003ctt\u003eThe WAVE generator\u003c/tt\u003e\u003c/p\u003e\u003cp\u003eOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone.\u003c/p\u003e\u003cp\u003e\u003ctt\u003eFor EXAMPLE\u003c/tt\u003e: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\u003c/p\u003e\u003cpre\u003e     1     1     1     1     1     1\r\n     1     2     2     2     2     2\r\n     1     2     3     3     3     3\r\n     1     2     3     4     4     4\r\n     1     2     3     4     5     5\r\n     1     2     3     4     5     6\u003c/pre\u003e","function_template":"function waves = WAVE(stone)\r\n  waves = stone;\r\nend","test_suite":"%%\r\nstone = 2;\r\nwaves =[1     1;\r\n        1     2];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 3;\r\nwaves =    [1     1     1;\r\n            1     2     2;\r\n            1     2     3];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 4;\r\nwaves =    [     1     1     1     1;\r\n                 1     2     2     2;\r\n                 1     2     3     3;\r\n                 1     2     3     4;];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 6;\r\nwaves =    [ 1     1     1     1     1     1;\r\n             1     2     2     2     2     2;\r\n             1     2     3     3     3     3;\r\n             1     2     3     4     4     4;\r\n             1     2     3     4     5     5;\r\n             1     2     3     4     5     6];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 10;\r\nwaves =    [   1     1     1     1     1     1     1     1     1     1;\r\n     1     2     2     2     2     2     2     2     2     2;\r\n     1     2     3     3     3     3     3     3     3     3;\r\n     1     2     3     4     4     4     4     4     4     4;\r\n     1     2     3     4     5     5     5     5     5     5;\r\n     1     2     3     4     5     6     6     6     6     6;\r\n     1     2     3     4     5     6     7     7     7     7;\r\n     1     2     3     4     5     6     7     8     8     8;\r\n     1     2     3     4     5     6     7     8     9     9;\r\n     1     2     3     4     5     6     7     8     9    10];\r\nassert(isequal( WAVE(stone),waves))","published":true,"deleted":false,"likes_count":15,"comments_count":2,"created_by":13514,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":349,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-07T09:32:28.000Z","updated_at":"2026-07-10T13:49:21.000Z","published_at":"2013-06-07T09:32:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eThe WAVE generator\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFor EXAMPLE\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[     1     1     1     1     1     1\\n     1     2     2     2     2     2\\n     1     2     3     3     3     3\\n     1     2     3     4     4     4\\n     1     2     3     4     5     5\\n     1     2     3     4     5     6]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1062,"title":"Three grind is shipsstraigt","description":"A function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests. ","description_html":"\u003cp\u003eA function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests.\u003c/p\u003e","function_template":"function y = driemaalisscheepsrecht()\r\n  y = 'Zizzors';\r\nend","test_suite":"%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));\r\n\r\n%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));\r\n\r\n%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":47,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-26T11:32:14.000Z","updated_at":"2026-07-20T10:44:23.000Z","published_at":"2012-11-26T11:39:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1052,"title":"Elapsed time is -0.005204 seconds.","description":"Write a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\r\n\r\n  tic\r\n  pause(1)\r\n  superfast()\r\n  toc\r\n\r\n  Elapsed time is 0.9876 seconds.","description_html":"\u003cp\u003eWrite a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003etic\r\npause(1)\r\nsuperfast()\r\ntoc\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eElapsed time is 0.9876 seconds.\r\n\u003c/pre\u003e","function_template":"function y = superfast(x)\r\n  pause(-1)\r\nend","test_suite":"%%\r\ntic\r\npause(1)\r\nsuperfast()\r\ntimeElapsed = toc;\r\nassert(timeElapsed \u003c 1)\r\n","published":true,"deleted":false,"likes_count":7,"comments_count":1,"created_by":450,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":105,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-23T21:59:46.000Z","updated_at":"2026-07-10T09:26:19.000Z","published_at":"2012-11-23T22:07:28.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[tic\\npause(1)\\nsuperfast()\\ntoc\\n\\nElapsed time is 0.9876 seconds.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43061,"title":"Chicken Race","description":"2 chickens, Pete and Fred, compete in a 100 meter race.\r\nPete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second.\r\nHowever, Fred cheats and starts before the starting shot, giving him an N seconds head start.\r\n\r\nWho wins the race? Answer 'Fred' or 'Pete'.","description_html":"\u003cp\u003e2 chickens, Pete and Fred, compete in a 100 meter race.\r\nPete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second.\r\nHowever, Fred cheats and starts before the starting shot, giving him an N seconds head start.\u003c/p\u003e\u003cp\u003eWho wins the race? Answer 'Fred' or 'Pete'.\u003c/p\u003e","function_template":"function winner = chickenRace(vf,vp,N)\r\n  winner = '???';\r\nend","test_suite":"%%%%\r\nvf = 5.5;\r\nvp = 6;\r\nN = 1;\r\nwinner = 'Pete';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n%%\r\nvf = 5.5;\r\nvp = 6;\r\nN = 2;\r\nwinner = 'Fred';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n%%\r\nvf = 6;\r\nvp = 6;\r\nN = 2;\r\nwinner = 'Fred';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":68,"test_suite_updated_at":"2016-10-19T11:44:40.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T14:26:25.000Z","updated_at":"2026-07-10T12:22:07.000Z","published_at":"2016-10-05T14:26:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e2 chickens, Pete and Fred, compete in a 100 meter race. Pete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second. However, Fred cheats and starts before the starting shot, giving him an N seconds head start.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWho wins the race? Answer 'Fred' or 'Pete'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2151,"title":"Reverse within string ","description":"If input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\r\n\r\nIf the length of the string is odd, leave the middle letter unchanged.\r\n\r\nInput 'letter' output 'telret'\r\n\r\nInput 'apple' output 'papel'","description_html":"\u003cp\u003eIf input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\u003c/p\u003e\u003cp\u003eIf the length of the string is odd, leave the middle letter unchanged.\u003c/p\u003e\u003cp\u003eInput 'letter' output 'telret'\u003c/p\u003e\u003cp\u003eInput 'apple' output 'papel'\u003c/p\u003e","function_template":"function y = reverse_within_string(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 'Help';\r\ny_correct = 'eHpl';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'between';\r\ny_correct = 'tebwnee';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'yellow';\r\ny_correct = 'leywol';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'apple';\r\ny_correct = 'papel';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'one, two, three';\r\ny_correct = 'wt ,enooeerht ,';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'red green blue';\r\ny_correct = 'erg dereulb ne';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'a';\r\ny_correct = 'a';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = '1234567890';\r\ny_correct = '5432109876';\r\nassert(isequal(reverse_within_string(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":22585,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":160,"test_suite_updated_at":"2017-09-27T15:43:07.000Z","rescore_all_solutions":false,"group_id":32,"created_at":"2014-02-05T10:25:53.000Z","updated_at":"2026-08-13T22:26:59.000Z","published_at":"2014-02-05T10:27:40.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the length of the string is odd, leave the middle letter unchanged.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput 'letter' output 'telret'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput 'apple' output 'papel'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44441,"title":"Jack's hand in \"Titanic\" ♤","description":"Given a series of cards, return true if it's the famous hand. Note that i pretend that  poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?","description_html":"\u003cp\u003eGiven a series of cards, return true if it's the famous hand. Note that i pretend that  poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m'); \r\nassert(isempty(strfind(filetext, 'regexp')),'regexp() and its family are forbidden') \r\nassert(isempty(strfind(filetext, 'regexprep')),'regexprep() forbidden')\r\n%%\r\nx = [10 3 10 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 8 1 7 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [10 5 10 5 10];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [4 4 6 3 5];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [2 4 2 4 4];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 9 9 9 9];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 7 8 7 8];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [nan 3 10 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [10 'k' 'j' 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 7 8 0 8];\r\ny_correct = false; %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 17 8 17 8] ;\r\ny_correct = false %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [0 7 0 7 0];\r\ny_correct = false; %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 3 3 8 3];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 .3 .3 8 .3];\r\ny_correct = false;  %invalid card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 1 1 5 5];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":"2017-12-09T11:50:03.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-06T14:41:25.000Z","updated_at":"2026-07-13T07:49:27.000Z","published_at":"2017-12-06T14:41:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a series of cards, return true if it's the famous hand. Note that i pretend that poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2002,"title":"Schrödinger dog","description":"Everyone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all? \r\n\r\nYES! NOW IT IS!\r\n\r\nYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet. ","description_html":"\u003cp\u003eEveryone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all?\u003c/p\u003e\u003cp\u003eYES! NOW IT IS!\u003c/p\u003e\u003cp\u003eYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet.\u003c/p\u003e","function_template":"function woof = dog\r\n  woof = true;\r\nend","test_suite":"%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = true;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = false;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 42;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = pi;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 'pie';\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = true;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = -1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 'woof';\r\nassert(isequal(dog('what is your name?'),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":"2013-11-16T23:37:42.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-16T23:29:45.000Z","updated_at":"2026-07-10T09:33:08.000Z","published_at":"2013-11-16T23:37:42.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEveryone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYES! NOW IT IS!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":45172,"title":"Cross (\"+\") flag returns","description":"Given two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\r\nGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of two numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\r\nFor example, [m, n] = [3, 3] would return:\r\n[0,1,0;\r\n1,1,1;\r\n0,1,0];\r\nAnd for even numbers: [p, q] = [4, 3] would return\r\n[0,1,0;\r\n1,1,1;\r\n1,1,1;\r\n0,1,0];","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 317.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 158.517px; transform-origin: 407px 158.517px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383px 8px; transform-origin: 383px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 279.5px 8px; transform-origin: 279.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12.5px 8px; transform-origin: 12.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 90px 8px; transform-origin: 90px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 127.5px 8px; transform-origin: 127.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, [m, n] = [3, 3] would return:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 30.65px; transform-origin: 404px 30.65px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[0,1,0;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0,1,0];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 155px 8px; transform-origin: 155px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAnd for even numbers: [p, q] = [4, 3] would return\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[0,1,0;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0,1,0];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = crossFlag2(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 2; n = 2;\r\ny_correct = zeros(2,2);\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 3; n = 3;\r\ny_correct = [0, 1, 0; 1, 1, 1; 0, 1, 0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 4; n = 4;\r\ny_correct = [0,1,1,0;\r\n             1,1,1,1;\r\n             1,1,1,1;\r\n             0,1,1,0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 5; n = 3;\r\ny_correct = [0, 1, 0; 0, 1, 0; 1, 1, 1; 0, 1, 0; 0, 1, 0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 3; n = 1;\r\ny_correct = ones(m,n);\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 16; n = 8;\r\ny_correct = [zeros(7,3),ones(7,2),zeros(7,3);ones(2,8);zeros(7,3),ones(7,2),zeros(7,3)];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 7; n = 280;\r\ny_correct = [zeros(3,139), ones(3,2), zeros(3,139); ones(1,280); zeros(3,139), ones(3,2), zeros(3,139)];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 1; n = 1;\r\ny_correct = 1;\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 0; n = 0;\r\ny_correct =[];\r\nassert(isequal(crossFlag2(m, n),y_correct));\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":8,"created_by":157354,"edited_by":223089,"edited_at":"2022-11-25T07:01:15.000Z","deleted_by":null,"deleted_at":null,"solvers_count":20,"test_suite_updated_at":"2022-11-25T07:01:15.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-11T20:16:53.000Z","updated_at":"2026-07-13T13:42:41.000Z","published_at":"2019-10-11T20:16:53.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etwo\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, [m, n] = [3, 3] would return:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[[0,1,0;\\n1,1,1;\\n0,1,0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd for even numbers: [p, q] = [4, 3] would return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[[0,1,0;\\n1,1,1;\\n1,1,1;\\n0,1,0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1713,"title":"Can you beat the lottery?","description":"Well this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\r\n\r\n    check = 1;\r\n    while check == 1\r\n        D1 = round(rand(1,1)*5+1);\r\n        D2 = round(rand(1,1)*5+1);\r\n        D3 = round(rand(1,1)*5+1);\r\n        draw = sort([D1 D2 D3]);\r\n        if size(unique(fn), 2) == 3\r\n            check = 0;\r\n        end\r\n    end\r\n\r\nSo \"draw\" is the draw that is made. It is made up of 3 numbers between 1 and 5.  Note that the numbers do not repeat.  SO an example of an input is:\r\n\r\nlottery = [4 3 5];\r\n\r\nNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...) \r\n\r\nGood luck, and please play responsibly...","description_html":"\u003cp\u003eWell this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\u003c/p\u003e\u003cpre\u003e    check = 1;\r\n    while check == 1\r\n        D1 = round(rand(1,1)*5+1);\r\n        D2 = round(rand(1,1)*5+1);\r\n        D3 = round(rand(1,1)*5+1);\r\n        draw = sort([D1 D2 D3]);\r\n        if size(unique(fn), 2) == 3\r\n            check = 0;\r\n        end\r\n    end\u003c/pre\u003e\u003cp\u003eSo \"draw\" is the draw that is made. It is made up of 3 numbers between 1 and 5.  Note that the numbers do not repeat.  SO an example of an input is:\u003c/p\u003e\u003cp\u003elottery = [4 3 5];\u003c/p\u003e\u003cp\u003eNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...)\u003c/p\u003e\u003cp\u003eGood luck, and please play responsibly...\u003c/p\u003e","function_template":"function draw = lottery()\r\n  draw = [x x x];\r\nend","test_suite":"%%\r\ncheck = 1;\r\nwhile check == 1\r\n     D1 = round(rand(1,1)*4+1);\r\n     D2 = round(rand(1,1)*4+1);\r\n     D3 = round(rand(1,1)*4+1);\r\n     draw = sort([D1 D2 D3]);\r\n        if size(unique(draw), 2) == 3\r\n            check = 0;\r\n        end\r\nend\r\nassert(isequal(sort(lottery()),draw))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":48,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-12T21:15:43.000Z","updated_at":"2025-11-17T20:59:24.000Z","published_at":"2013-07-12T22:07:45.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    check = 1;\\n    while check == 1\\n        D1 = round(rand(1,1)*5+1);\\n        D2 = round(rand(1,1)*5+1);\\n        D3 = round(rand(1,1)*5+1);\\n        draw = sort([D1 D2 D3]);\\n        if size(unique(fn), 2) == 3\\n            check = 0;\\n        end\\n    end]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo \\\"draw\\\" is the draw that is made. It is made up of 3 numbers between 1 and 5. Note that the numbers do not repeat. SO an example of an input is:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003elottery = [4 3 5];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGood luck, and please play responsibly...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1687,"title":"Poker Card Deal!","description":"Anyone want to play a card game?  \r\n\r\nWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards.  Rows are the amount of people in play, columns are the amount of cards dealt to each person.  The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\r\n\r\nThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J.  The suits are s for spades, d for dimonds, h for hearts and c for clubs.  \r\n\r\nSo the final cards look like this:\r\n\r\n'js'\r\n\r\n'J'\r\n\r\n'2h'\r\n\r\n'ad'\r\n\r\n'5c' and so on.\r\n\r\nThis function reads in three variables, these are:\r\n\r\npeople -- This is the amount of people that the cards are being dealt to.\r\n\r\ncardsDelt  -- This is the amount of cards dealt to each person.\r\n\r\nisJokerIn --  This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\r\n\r\nso an example is the following, if the variables are:\r\n\r\n%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\r\n\r\npeople = 5;\r\n\r\ncardsDelt = 5; %note, this is a typical deal for a poker game...\r\n\r\nisJokerIn = 0; \r\n\r\nThe outputs will be:\r\n\r\ndealtDeck = \r\n\r\n    'qh'    'as'    '5s'     '2s'    'jd' \r\n    'ad'    '5d'    '9s'     '7h'    'ah' \r\n    '3c'    '2d'    'ac'     '8c'    'qd' \r\n    'kh'    '5h'    '4c'     '3h'    '10s'\r\n    '6h'    '8h'    '10c'    '4s'    '8d' \r\n\r\n%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\r\n\r\ndeckLeftover = \r\n\r\n    '3s'\r\n    '4h'\r\n    '2c'\r\n    '5c'\r\n    'qs'\r\n    'jh'\r\n    'kd'\r\n    '2h'\r\n    '9c'\r\n    '10h'\r\n    '9h'\r\n    '6d'\r\n    '7c'\r\n    '7s'\r\n    '8s'\r\n    'qc'\r\n    'js'\r\n    '9d'\r\n    '7d'\r\n    'ks'\r\n    '6c'\r\n    '6s'\r\n    '3d'\r\n    '10d'\r\n    'jc'\r\n    '4d'\r\n    'kc'\r\n\r\nWell I hope that everyone has fun with it!  Thank you!\r\n\r\n","description_html":"\u003cp\u003eAnyone want to play a card game?\u003c/p\u003e\u003cp\u003eWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards.  Rows are the amount of people in play, columns are the amount of cards dealt to each person.  The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\u003c/p\u003e\u003cp\u003eThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J.  The suits are s for spades, d for dimonds, h for hearts and c for clubs.\u003c/p\u003e\u003cp\u003eSo the final cards look like this:\u003c/p\u003e\u003cp\u003e'js'\u003c/p\u003e\u003cp\u003e'J'\u003c/p\u003e\u003cp\u003e'2h'\u003c/p\u003e\u003cp\u003e'ad'\u003c/p\u003e\u003cp\u003e'5c' and so on.\u003c/p\u003e\u003cp\u003eThis function reads in three variables, these are:\u003c/p\u003e\u003cp\u003epeople -- This is the amount of people that the cards are being dealt to.\u003c/p\u003e\u003cp\u003ecardsDelt  -- This is the amount of cards dealt to each person.\u003c/p\u003e\u003cp\u003eisJokerIn --  This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\u003c/p\u003e\u003cp\u003eso an example is the following, if the variables are:\u003c/p\u003e\u003cp\u003e%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\u003c/p\u003e\u003cp\u003epeople = 5;\u003c/p\u003e\u003cp\u003ecardsDelt = 5; %note, this is a typical deal for a poker game...\u003c/p\u003e\u003cp\u003eisJokerIn = 0;\u003c/p\u003e\u003cp\u003eThe outputs will be:\u003c/p\u003e\u003cp\u003edealtDeck =\u003c/p\u003e\u003cpre\u003e    'qh'    'as'    '5s'     '2s'    'jd' \r\n    'ad'    '5d'    '9s'     '7h'    'ah' \r\n    '3c'    '2d'    'ac'     '8c'    'qd' \r\n    'kh'    '5h'    '4c'     '3h'    '10s'\r\n    '6h'    '8h'    '10c'    '4s'    '8d' \u003c/pre\u003e\u003cp\u003e%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\u003c/p\u003e\u003cp\u003edeckLeftover =\u003c/p\u003e\u003cpre\u003e    '3s'\r\n    '4h'\r\n    '2c'\r\n    '5c'\r\n    'qs'\r\n    'jh'\r\n    'kd'\r\n    '2h'\r\n    '9c'\r\n    '10h'\r\n    '9h'\r\n    '6d'\r\n    '7c'\r\n    '7s'\r\n    '8s'\r\n    'qc'\r\n    'js'\r\n    '9d'\r\n    '7d'\r\n    'ks'\r\n    '6c'\r\n    '6s'\r\n    '3d'\r\n    '10d'\r\n    'jc'\r\n    '4d'\r\n    'kc'\u003c/pre\u003e\u003cp\u003eWell I hope that everyone has fun with it!  Thank you!\u003c/p\u003e","function_template":"function [dealtDeck, deckLeftover] = Poker_Deal(people,cardsDelt,isJokerIn)\r\ndealtDeck ='this is the dealt deck to players'\r\ndeckLeftover = 'is the left over cards in the deck, after being delt'\r\nend","test_suite":"%%\r\npeople = 5;\r\ncardsDelt = 5;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 25) \u0026 ~issorted(reshape(dealtDeck,25,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-25)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 5;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 15) \u0026 ~issorted(reshape(dealtDeck,15,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-15)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 4;\r\ncardsDelt = 7;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 28) \u0026 ~issorted(reshape(dealtDeck,28,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-28)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 5;\r\ncardsDelt = 6;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'; 'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 30) \u0026 ~issorted(reshape(dealtDeck,30,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-30)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 4;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'; 'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 12) \u0026 ~issorted(reshape(dealtDeck,12,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-12)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 3;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac';  'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 9) \u0026 ~issorted(reshape(dealtDeck,9,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-9)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":15,"created_at":"2013-06-30T01:06:43.000Z","updated_at":"2026-08-12T15:56:02.000Z","published_at":"2013-06-30T01:06:43.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnyone want to play a card game?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards. Rows are the amount of people in play, columns are the amount of cards dealt to each person. The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J. The suits are s for spades, d for dimonds, h for hearts and c for clubs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo the final cards look like this:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'js'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'J'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'2h'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'ad'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'5c' and so on.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis function reads in three variables, these are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003epeople -- This is the amount of people that the cards are being dealt to.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ecardsDelt -- This is the amount of cards dealt to each person.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eisJokerIn -- This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso an example is the following, if the variables are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003epeople = 5;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ecardsDelt = 5; %note, this is a typical deal for a poker game...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eisJokerIn = 0;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe outputs will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003edealtDeck =\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    'qh'    'as'    '5s'     '2s'    'jd' \\n    'ad'    '5d'    '9s'     '7h'    'ah' \\n    '3c'    '2d'    'ac'     '8c'    'qd' \\n    'kh'    '5h'    '4c'     '3h'    '10s'\\n    '6h'    '8h'    '10c'    '4s'    '8d']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003edeckLeftover =\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    '3s'\\n    '4h'\\n    '2c'\\n    '5c'\\n    'qs'\\n    'jh'\\n    'kd'\\n    '2h'\\n    '9c'\\n    '10h'\\n    '9h'\\n    '6d'\\n    '7c'\\n    '7s'\\n    '8s'\\n    'qc'\\n    'js'\\n    '9d'\\n    '7d'\\n    'ks'\\n    '6c'\\n    '6s'\\n    '3d'\\n    '10d'\\n    'jc'\\n    '4d'\\n    'kc']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell I hope that everyone has fun with it! Thank you!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2459,"title":"grazing cows","description":"Here is a fun problem I encountered in high school.\r\n\r\nTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.","description_html":"\u003cp\u003eHere is a fun problem I encountered in high school.\u003c/p\u003e\u003cp\u003eTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.\u003c/p\u003e","function_template":"function y = graze(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 0.9566\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 2;\r\ny_correct = 3.8264;\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 6;\r\ny_correct = 34.4380;\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 9;\r\ny_correct = 77.4855;\r\nassert(isequal(graze(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":4,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-07-23T11:07:08.000Z","updated_at":"2026-07-21T08:42:06.000Z","published_at":"2014-07-23T11:07:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHere is a fun problem I encountered in high school.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1003,"title":"Make a KITT-scanner on the command line","description":"Did you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with |fprintf(char(8));| (ASCII code 8 is a backspace), and the last character is removed. \r\nThis way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with   \r\n\r\n fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));\r\n\r\nYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. \r\nThe characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example \r\n\r\n kitt(10,'#=~-')\r\n\r\ntells it to show up as\r\n\r\n '#=~-------'\r\n\r\nIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\r\n\r\n '=#--------'\r\n\r\nfollowed by \r\n\r\n '~=#-------'\r\n\r\nand \r\n\r\n '-~=#------'\r\n\r\nand so on.\r\nYou see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S.\r\nThe 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen.\r\nTo check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). \r\nAnd off course, try to avoid just hard-coding the result. ","description_html":"\u003cp\u003eDid you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with \u003ctt\u003efprintf(char(8));\u003c/tt\u003e (ASCII code 8 is a backspace), and the last character is removed. \r\nThis way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with\u003c/p\u003e\u003cpre\u003e fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));\u003c/pre\u003e\u003cp\u003eYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. \r\nThe characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example\u003c/p\u003e\u003cpre\u003e kitt(10,'#=~-')\u003c/pre\u003e\u003cp\u003etells it to show up as\u003c/p\u003e\u003cpre\u003e '#=~-------'\u003c/pre\u003e\u003cp\u003eIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\u003c/p\u003e\u003cpre\u003e '=#--------'\u003c/pre\u003e\u003cp\u003efollowed by\u003c/p\u003e\u003cpre\u003e '~=#-------'\u003c/pre\u003e\u003cp\u003eand\u003c/p\u003e\u003cpre\u003e '-~=#------'\u003c/pre\u003e\u003cp\u003eand so on.\r\nYou see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S.\r\nThe 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen.\r\nTo check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). \r\nAnd off course, try to avoid just hard-coding the result.\u003c/p\u003e","function_template":"function scanner = kitt(l,s)\r\n  scanner = [s repmat(s(end),1,l-length(s))];\r\n  fprintf(scanner);\r\n  pause(2000/l);\r\n  fprintf(repmat([char(8) ' ' char(8)],1,l));\r\nend","test_suite":"%%\r\nl = 5;\r\ns = '#=~-';\r\ny_correct = strvcat({\r\n   '#=~--'\r\n   '=#---'\r\n   '~=#--'\r\n   '-~=#-'\r\n   '--~=#'\r\n   '---#='\r\n   '--#=~'\r\n   '-#=~-'\r\n   '#=~--'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 2;\r\ns = '*';\r\ny_correct = strvcat({\r\n   '**'\r\n   '**'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 5;\r\ns = '@ ';\r\ny_correct = strvcat({\r\n   '@    '\r\n   ' @   '\r\n   '  @  '\r\n   '   @ '\r\n   '    @'\r\n   '   @ '\r\n   '  @  '\r\n   ' @   '\r\n   '@    '\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 6;\r\ns = '@\u003e\u003e*=~ ';\r\ny_correct = strvcat({\r\n   '@\u003e\u003e*=~'\r\n   '\u003e@*=~ '\r\n   '\u003e\u003e@~  '\r\n   '*\u003e\u003e@  '\r\n   '=*\u003e\u003e@ '\r\n   '~=*\u003e\u003e@'\r\n   ' ~=*@\u003e'\r\n   '  ~@\u003e\u003e'\r\n   '  @\u003e\u003e*'\r\n   ' @\u003e\u003e*='\r\n   '@\u003e\u003e*=~'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2012-10-30T08:09:52.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-10-19T05:48:39.000Z","updated_at":"2026-08-25T21:42:35.000Z","published_at":"2012-10-19T05:52:44.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDid you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efprintf(char(8));\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (ASCII code 8 is a backspace), and the last character is removed. This way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. The characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ kitt(10,'#=~-')]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003etells it to show up as\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '#=~-------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '=#--------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efollowed by\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '~=#-------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '-~=#------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand so on. You see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S. The 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen. To check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). And off course, try to avoid just hard-coding the result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1696,"title":"Morse Code Generator! Try it!","description":"  .... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \r\n        .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \r\n  \r\n\r\n\r\n  \r\n\r\n  text = 'Morse code is FUN!'\r\n  Morse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--'\r\n\r\n\r\nJust a note: this uses international style Morse code found in:\r\n\r\nhttp://en.wikipedia.org/wiki/American_Morse_code\r\n","description_html":"\u003cpre class=\"language-matlab\"\u003e.... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \r\n      .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003etext = 'Morse code is FUN!'\r\nMorse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--'\r\n\u003c/pre\u003e\u003cp\u003eJust a note: this uses international style Morse code found in:\u003c/p\u003e\u003cp\u003e\u003ca href = \"http://en.wikipedia.org/wiki/American_Morse_code\"\u003ehttp://en.wikipedia.org/wiki/American_Morse_code\u003c/a\u003e\u003c/p\u003e","function_template":"function Morse_code_out = MorseCodeGenerator(text)\r\n  Morse_code_out = text_in;\r\nend","test_suite":"%%\r\nx = 'Morse code is FUN!';\r\ny_correct = '-- --- .-. ... .     -.-. --- -.. .     .. ...     ..-. ..- -. -.-.--';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = 'Am I 20, (who knows?)';\r\ny_correct = '.- --     ..     ..--- ----- --..--     -.--. .-- .... ---     -.- -. --- .-- ... ..--.. -.--.-';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = 'THE QUICK BROWN FOX JUMPS OVER THE LAZY DOG: or does he...';\r\ny_correct = '- .... .     --.- ..- .. -.-. -.-     -... .-. --- .-- -.     ..-. --- -..-     .--- ..- -- .--. ...     --- ...- . .-.     - .... .     .-.. .- --.. -.--     -.. --- --. ---...     --- .-.     -.. --- . ...     .... . .-.-.- .-.-.- .-.-.-';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = '1234567890';\r\ny_correct = '.---- ..--- ...-- ....- ..... -.... --... ---.. ----. -----';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":95,"test_suite_updated_at":"2019-09-16T11:37:52.000Z","rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-05T18:50:09.000Z","updated_at":"2026-07-15T14:09:32.000Z","published_at":"2013-07-09T15:55:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[.... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \\n      .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \\n\\ntext = 'Morse code is FUN!'\\nMorse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eJust a note: this uses international style Morse code found in:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/American_Morse_code\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://en.wikipedia.org/wiki/American_Morse_code\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1721,"title":"Backslang, odds are you used it at some point in time...","description":"So backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it.  Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end. \r\n\r\nHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\r\n\r\n  str = 'The sky is falling, the sky is falling, or is it?'\r\n\r\n  output = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?\r\n\r\nUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\r\n\r\nOodgay Ucklay!","description_html":"\u003cp\u003eSo backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it.  Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end.\u003c/p\u003e\u003cp\u003eHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003estr = 'The sky is falling, the sky is falling, or is it?'\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eoutput = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?\r\n\u003c/pre\u003e\u003cp\u003eUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\u003c/p\u003e\u003cp\u003eOodgay Ucklay!\u003c/p\u003e","function_template":"function output = backslang(str)\r\n  output = str;\r\nend","test_suite":"%%\r\nstr = 'The sky is falling, the sky is falling, or is it?'\r\noutput = 'Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'If Allen is Janes husband and Tom is Jill husband, who is Roys wife?'\r\noutput = 'Fiay Llenaay siay Anesjay usbandhay ndaay Omtay siay Illjay usbandhay, howay siay Oysray ifeway?'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'This is the sentence I will use.'\r\noutput = 'Histay siay hetay entencesay Iay illway seuay.'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'Christopher Columbus sailed the ocean blue!'\r\noutput = 'Hristophercay Olumbuscay ailedsay hetay ceanoay luebay!'\r\nassert(isequal(backslang(str),output))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":85,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-17T16:39:49.000Z","updated_at":"2026-07-15T14:00:40.000Z","published_at":"2013-07-17T16:39:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it. Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[str = 'The sky is falling, the sky is falling, or is it?'\\n\\noutput = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOodgay Ucklay!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":53064,"title":"Amazing circle of numbers 1 to n","description":"For given natural number n, create amazing circle of numbers 1 to n without a repeat.\r\nThis circle is that the sum of any two adjacent numbers is a perfect square.\r\nFor example, if n = 32,\r\n\r\nSo, output is\r\n                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\r\nIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\r\nIf there is no amazing circle vector, return empty vector [].","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 984px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 492px; transform-origin: 407px 492px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor given natural number n, create amazing circle of numbers 1 to n without a repeat.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis circle is that the sum of any two adjacent numbers is a perfect square.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if n = 32,\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 774px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 387px; text-align: left; transform-origin: 384px 387px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"768\" height=\"768\" style=\"vertical-align: baseline;width: 768px;height: 768px\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSo, output is\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIf there is no amazing circle vector, return empty vector [].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = amazing_circle(n)\r\n  v = n;\r\nend","test_suite":"%%\r\nn=32;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=33;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=34;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=35;\r\nv = amazing_circle(n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=36;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=37;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=38;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":517609,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2021-11-29T05:26:18.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2021-11-15T02:36:58.000Z","updated_at":"2026-09-17T23:13:59.000Z","published_at":"2021-11-15T04:44:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor given natural number n, create amazing circle of numbers 1 to n without a repeat.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis circle is that the sum of any two adjacent numbers is a perfect square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, if n = 32,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"768\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"768\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo, output is\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf there is no amazing circle vector, return empty vector 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":43574,"title":"Connect 4 (the boardgame)","description":"You are playing the popular game \"Connect 4\" ( \u003chttps://en.wikipedia.org/wiki/Connect_Four\u003e) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\r\n\r\nWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\r\n\r\nEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \"1\" (a chip of your opponent), \"2\" (one of your chips) or \"0\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\r\n\r\nGood luck!","description_html":"\u003cp\u003eYou are playing the popular game \"Connect 4\" ( \u003ca href = \"https://en.wikipedia.org/wiki/Connect_Four\"\u003ehttps://en.wikipedia.org/wiki/Connect_Four\u003c/a\u003e) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\u003c/p\u003e\u003cp\u003eWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\u003c/p\u003e\u003cp\u003eEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \"1\" (a chip of your opponent), \"2\" (one of your chips) or \"0\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\u003c/p\u003e\u003cp\u003eGood luck!\u003c/p\u003e","function_template":"function c = move(board)\r\n    % - the input board is a 5x7 matrix containing 0,1,2: The elements 0 are\r\n    % empty spaces, 1 are chips of your opponent and 2 are your chipt.\r\n    % - the output c is the column of your next chip, make sure this column\r\n    % has space left for your chip or the turn goes lost!\r\n\r\n    % select random available column\r\n    allC = find(sum(board~=0,1)\u003c5,7); % all not yet full columns\r\n    c = allC(randi(length(allC),1,1)); % random placement\r\nend","test_suite":"%%\r\ngames = 10;\r\nwinners = zeros(games,1);\r\nfor gamenum = 1:games % you play \"games\" different games\r\n    % init the board\r\n    board = zeros(5,7);\r\n    % function finding the index at which the chip will fall in column c\r\n    index = @(c,board) find(board(:,c)==0,1,'last');\r\n    % start the game\r\n    whoWon = 0;\r\n    done = false;\r\n    turn = 1;\r\n    while done == false\r\n        if turn == 1 % you oppenent's turn\r\n            % select random column\r\n            allC = find(sum(board~=0,1)\u003c5,7); % all not full columns\r\n            c = allC(randi(length(allC),1,1)); % random placement\r\n            % place chip in column c\r\n            board(index(c,board),c) = 1;\r\n        else % your turn\r\n            % which column\r\n            c = move(board);\r\n            % place chip in column c\r\n            i = index(c,board); % index\r\n            if ~isempty(i)\r\n                board(i,c) = 2;\r\n            else\r\n                disp('You have selected a full column, your turn goes lost')\r\n            end\r\n        end\r\n\r\n        % check for a 4-in-a-row\r\n        temp = board==turn;\r\n        % gather all possible 4-in-a-row lines\r\n            lines = cell(22,1);\r\n            % horizontal\r\n            for i = 1:5\r\n                lines{i} = temp(i,:)';\r\n            end\r\n            % vertical\r\n            for i = 1:7\r\n                lines{i+5} = temp(:,i);\r\n            end\r\n            % diagonal \\\r\n            lines{13} = diag(temp(2:end,:));\r\n            for i = 1:4\r\n                lines{i+13} = diag(temp(:,i:end));\r\n            end\r\n            % diagonal /\r\n            temp = fliplr(temp);\r\n            lines{18} = diag(temp(2:end,:));\r\n            for i = 1:4\r\n                lines{i+18} = diag(temp(:,i:end));\r\n            end\r\n        for i = 1:length(lines)\r\n            % find the maximum number of the same chips in this row\r\n            temp = diff([0; lines{i}; 0]);\r\n            if max(find(temp==-1,7)-find(temp==1,7))==4\r\n                % game is won!\r\n                whoWon = turn;\r\n                done = true;\r\n            end\r\n        end\r\n        % is the board full without a winner?\r\n        if sum(board==0)==0\r\n            done = true;\r\n        end\r\n        % switch turns\r\n        turn = 3-turn;\r\n    end % end of one game\r\n    winners(gamenum) = whoWon;\r\nend\r\ndisp(['Game results (#won/#lost/#draw): ' num2str(sum(winners==2)) '/' num2str(sum(winners==1)) '/' num2str(sum(winners==0))])\r\n% Did you win all 10 games?\r\nassert(isequal(sum(winners==2),games))","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-18T09:14:38.000Z","updated_at":"2026-05-25T01:57:26.000Z","published_at":"2016-10-18T09:14:38.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are playing the popular game \\\"Connect 4\\\" (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Connect_Four\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://en.wikipedia.org/wiki/Connect_Four\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \\\"1\\\" (a chip of your opponent), \\\"2\\\" (one of your chips) or \\\"0\\\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGood luck!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"}],"problem_search":{"problems":[{"id":44688,"title":"World Cup 2018 Prediction!","description":"Which team will be the winner?\r\n","description_html":"\u003cp\u003eWhich team will be the winner?\u003c/p\u003e","function_template":"function y = Worldcup2018winner()\r\n  y = \"????\"\r\nend","test_suite":"%%\r\nteams={'Russia','Saudi Arabia', 'Egypt', 'Uruguay', 'Portugal', 'Spain','Morocco','Iran',...\r\n    'France','Australia', 'Peru','Denmark', 'Brazil', 'Switzerland', 'Costa Rica', 'Serbia', ...\r\n    'Germany', 'Mexico', 'Sweden', 'STH Korea', 'Belgium', 'Panama', 'Tunisia', 'England' , ...\r\n    'Argentina','Iceland', 'Croatia', 'Nigeria', 'Poland', 'Senegal', 'Colombia', 'Japan'};\r\nd=false;\r\nfor i=1:numel(teams)\r\n    if strcmp(Worldcup2018winner(),teams{i})\r\n        d=true;\r\n        break;\r\n    end\r\nend\r\nassert(d)","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":218677,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":146,"test_suite_updated_at":"2018-06-15T17:39:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-06-15T17:38:14.000Z","updated_at":"2026-09-18T04:03:23.000Z","published_at":"2018-06-15T17:38:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhich team will be the winner?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":60956,"title":"P(girl likes you | she smiled at you)","description":"Compute the probability\r\n\r\n\r\n\r\nGiven the input probabilities\r\n\r\n\r\n\r\n\r\n\r\n\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 401.867px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 408px 200.933px; transform-origin: 408px 200.933px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 80.4833px 8px; transform-origin: 80.4833px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eCompute the probability\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; 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width=\"283.5\" height=\"20\" style=\"width: 283.5px; height: 20px;\"\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 94.4667px 8px; transform-origin: 94.4667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eGiven the input probabilities\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv 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width=\"224\" height=\"20\" style=\"width: 224px; height: 20px;\"\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function P_LS = verify_bayes_theorem(P_SL, P_L, P_S)\r\n  P_LS = P_SL;\r\nend","test_suite":"%%\r\nP_SL = 0.99;\r\nP_L  = 1/3;\r\nP_S  = 0.5;\r\nP_LS_correct = 0.66;\r\nP_LS = verify_bayes_theorem(P_SL,P_L,P_S);\r\nassert(abs(P_LS_correct-P_LS) \u003c eps)\r\n\r\n%%\r\nP_SL = 0.75;\r\nP_L  = 1/5;\r\nP_S  = 0.25;\r\nP_LS_correct = 0.6;\r\nP_LS = verify_bayes_theorem(P_SL,P_L,P_S);\r\nassert(abs(P_LS_correct-P_LS) \u003c eps)\r\n\r\n%% Test forbidden functions\r\nfiletext = fileread('verify_bayes_theorem.m');\r\nillegal = contains(filetext, 'regexp') || contains(filetext, 'str2num') || contains(filetext, 'assignin') || contains(filetext, 'echo')\r\nassert(~illegal);","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":149128,"edited_by":149128,"edited_at":"2025-07-10T07:02:07.000Z","deleted_by":null,"deleted_at":null,"solvers_count":46,"test_suite_updated_at":"2025-07-10T07:02:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2025-07-08T12:54:24.000Z","updated_at":"2026-09-14T06:34:16.000Z","published_at":"2025-07-08T13:17:57.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCompute the probability\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_{LS} = P(girl ~likes ~ you ~ | ~ she ~ smiled ~ at ~ you) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGiven the input probabilities\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_{SL} = P(she ~ smiles ~ at ~ you ~ | ~ she ~ likes ~ you)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_L = P(she ~likes ~ you) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eP_S = P(she ~ just ~ smiles ~ in ~ general) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44493,"title":"The great 82-year-old","description":"Let's answer the question below;\r\n\r\n'I am *x* years old and I have never written programs.\r\nIf I study from now, will I be able to develop programs?'\r\n\r\ninput *x* (years old) \u003e\u003e\u003e output 'Yes' or 'No'","description_html":"\u003cp\u003eLet's answer the question below;\u003c/p\u003e\u003cp\u003e'I am \u003cb\u003ex\u003c/b\u003e years old and I have never written programs.\r\nIf I study from now, will I be able to develop programs?'\u003c/p\u003e\u003cp\u003einput \u003cb\u003ex\u003c/b\u003e (years old) \u0026gt;\u0026gt;\u0026gt; output 'Yes' or 'No'\u003c/p\u003e","function_template":"function Answer = Age(x)\r\n  Answer = 'Yes';\r\nend","test_suite":"%%\r\nx = 20;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))\r\n%%\r\nx = 40;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))\r\n%% Great Ms Masako Wakamiya\r\nx = 82-1;\r\ny_correct = 'Yes';\r\nassert(isequal(Age(x),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":137687,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":154,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2018-01-08T12:47:36.000Z","updated_at":"2026-08-20T13:44:45.000Z","published_at":"2018-01-08T12:58:55.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLet's answer the question below;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'I am\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e years old and I have never written programs. If I study from now, will I be able to develop programs?'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (years old) \u0026gt;\u0026gt;\u0026gt; output 'Yes' or 'No'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43747,"title":"Find the distance traveled by a car given velocity and time.","description":"A car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.","description_html":"\u003cp\u003eA car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.\u003c/p\u003e","function_template":"function y = distance(velocity,time)\r\n  D = time;\r\nend","test_suite":"%%\r\nvelocity = 10;\r\ntime = 60; \r\nD_correct = 600;\r\nassert(isequal(distance(velocity,time),D_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":100857,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":130,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-07T20:05:40.000Z","updated_at":"2026-02-10T21:28:41.000Z","published_at":"2016-12-07T20:05:40.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA car is traveling at a constant velocity for a specific amount of time. The function should use the two inputs, velocity and time, to find the distance traveled.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44413,"title":"determine amount cookies left","description":"started with 3 cookies and you never ate any how many are left","description_html":"\u003cp\u003estarted with 3 cookies and you never ate any how many are left\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 3;\r\ny_correct = 3;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":157993,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":133,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-11-24T06:51:36.000Z","updated_at":"2026-05-29T03:47:36.000Z","published_at":"2017-11-24T06:51:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003estarted with 3 cookies and you never ate any how many are left\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43557,"title":"Find hen's weight. ","description":"If hen weights x kilos on two legs, how much does it weights on one leg? Output the result.","description_html":"\u003cp\u003eIf hen weights x kilos on two legs, how much does it weights on one leg? Output the result.\u003c/p\u003e","function_template":"function y = Hen(x)\r\n  y = x-x+2*x+x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1-1+1-1-1+1+1-1+1-1+1-1+1;\r\nassert(isequal(Hen(x),y_correct))\r\n%%\r\nx = 2;\r\ny_correct = 1-1+1-1-1+1+1-1+1-1+1-1+1+1;\r\nassert(isequal(Hen(x),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":90467,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":138,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-15T10:07:55.000Z","updated_at":"2026-03-09T20:47:23.000Z","published_at":"2016-10-15T10:07:55.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf hen weights x kilos on two legs, how much does it weights on one leg? Output the result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":48015,"title":"Calculate the volume of the football","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63.9631px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.989px 31.9744px; transform-origin: 406.996px 31.9815px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9091px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.991px 10.4545px; text-align: left; transform-origin: 383.999px 10.4545px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the volume of a football given the ball radius r, using the formula below:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 34.0625px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.991px 17.0312px; text-align: left; transform-origin: 383.999px 17.0312px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg 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encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the volume of a football given the ball radius r, using the formula below:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eV_{sphere} = \\\\frac43 \\\\pi 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45-3;\r\nassert(isequal(TheAnswer(),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":14644,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":119,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-07T09:17:52.000Z","updated_at":"2026-02-12T18:40:12.000Z","published_at":"2016-10-07T09:17:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml 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?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":304,"title":"Bottles of beer","description":"Given an input number representing the number of bottles of beer on the wall, output how many are left if you take one down and pass it around.","description_html":"\u003cp\u003eGiven an input number representing the number of bottles of beer on the wall, output how many are left if you take one down and pass it around.\u003c/p\u003e","function_template":"function remaining = bottles_of_beer(on_the_wall)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 99;\r\ny_correct = 98;\r\nassert(isequal(bottles_of_beer(x),y_correct))\r\n\r\n%%\r\nx = 9;\r\ny_correct = 8;\r\nassert(isequal(bottles_of_beer(x),y_correct))\r\n\r\n%%\r\nx = 1;\r\ny_correct = 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type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44664,"title":"function to compute root mean square of first nn positive odd integers","description":"Write a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 84px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 42px; transform-origin: 407px 42px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 367px 8px; transform-origin: 367px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function orms = odd_rms(nn)\r\n  \r\nend","test_suite":"%%\r\nnn = 3;\r\norms_correct = 3.4156\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)\r\n\r\n%%\r\nnn = 10;\r\norms_correct = 11.5325\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)\r\n\r\n%%\r\nnn = 1;\r\norms_correct = 1\r\nassert(abs(odd_rms(nn)-orms_correct)\u003c0.5)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":171559,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":59,"test_suite_updated_at":"2021-12-31T17:41:47.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-05-29T15:13:46.000Z","updated_at":"2026-05-30T00:36:27.000Z","published_at":"2018-05-29T15:13:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function called odd_rms that returns orms, which is the square root of the mean of the squares of the first nn positive odd integers, where nn is a positive integer and is the only input argument. For example, if nn is 3, your function needs to compute and return the square root of the average of the numbers 1, 9, and 25. You may use built-in functions including, for example, sum and sqrt, except for the built-in function rms, which is not allowed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42632,"title":"Your favourite city!","description":"Type your favourite city.","description_html":"\u003cp\u003eType your favourite city.\u003c/p\u003e","function_template":"function y = favoriteCity()\r\n  y = '';\r\nend","test_suite":"%%\r\nassert(ischar(favoriteCity()))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":319,"test_suite_updated_at":"2015-09-23T05:22:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-09-23T05:19:30.000Z","updated_at":"2026-06-05T09:36:48.000Z","published_at":"2015-09-23T05:19:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eType your favourite city.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":748,"title":"Wrapping the Tower of Pisa","description":"The famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\r\n\r\nNote: inspired on problem 167","description_html":"\u003cp\u003eThe famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\u003c/p\u003e\u003cp\u003eNote: inspired on problem 167\u003c/p\u003e","function_template":"function y = paperneed(s,a)\r\n  y = s;\r\nend","test_suite":"%%\r\ns = pi;\r\na = pi^2;\r\ny_correct = 2*pi^4 + pi^3;\r\nassert(abs(paperneed(s,a)-y_correct)\u003c1e-12)\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":5,"created_by":4638,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":303,"test_suite_updated_at":"2012-06-06T20:53:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-05T11:41:10.000Z","updated_at":"2026-06-05T12:21:14.000Z","published_at":"2012-06-05T11:41:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe famous artist Christo Vladimirov Javacheff, who likes pizza, wants to wrap the well-known Italian tower in paper. It is a circular tower with radius s [m] and height a [m] and he decided to neglect the fact that it was leaning. How many square meters of paper should he bring as a minimum? Don't forget the top, although it is not so nice!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: inspired on problem 167\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2053,"title":"Strange Number Algorithms","description":"Three integer numbers will be provided to you. Write a function to \r\n\r\n Step1: Multiply first number by 3.\r\n Step2: Add 6 with the getting result.\r\n Step3: divide it by 3.\r\n Step4: Subtract the first number.\r\n\r\n Step1: Double the second number.\r\n Step2: Add 9 with result.\r\n Step3: Subtract 3 with the result.\r\n Step4: Divide the result by 2.\r\n Step5: Subtract the result with the second number.\r\n\r\n Step1:Add 7 to the third number.\r\n Step2:Multiply the number with 2.\r\n Step3:Subtract 4 from the result.\r\n Step4:Divide the result by 2.\r\n Step5:Subtract the third number from the result.\r\n\r\nReturn a single row matrix with the three answers.\r\n\r\n","description_html":"\u003cp\u003eThree integer numbers will be provided to you. Write a function to\u003c/p\u003e\u003cpre\u003e Step1: Multiply first number by 3.\r\n Step2: Add 6 with the getting result.\r\n Step3: divide it by 3.\r\n Step4: Subtract the first number.\u003c/pre\u003e\u003cpre\u003e Step1: Double the second number.\r\n Step2: Add 9 with result.\r\n Step3: Subtract 3 with the result.\r\n Step4: Divide the result by 2.\r\n Step5: Subtract the result with the second number.\u003c/pre\u003e\u003cpre\u003e Step1:Add 7 to the third number.\r\n Step2:Multiply the number with 2.\r\n Step3:Subtract 4 from the result.\r\n Step4:Divide the result by 2.\r\n Step5:Subtract the third number from the result.\u003c/pre\u003e\u003cp\u003eReturn a single row matrix with the three answers.\u003c/p\u003e","function_template":"function amat = strange(n)\r\n  amat = n(1)-n(1)*3+6/3;\r\nend","test_suite":"%%\r\nn = [1 10 100];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [0 499 999];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [999 666 333];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n%%\r\nn = [7 63 347];\r\na(1)=(((n(1)*3)+6)/3)-n(1);\r\na(2)=(((n(2)*2)+9)-3)/2-n(2);\r\na(3)=(((n(3)+7)*2)-4)/2-n(3);\r\ny_correct = a;\r\nassert(isequal(strange(n),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":17471,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":101,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-12-15T06:55:46.000Z","updated_at":"2026-02-20T14:09:20.000Z","published_at":"2013-12-15T06:56:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThree integer numbers will be provided to you. Write a function to\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ Step1: Multiply first number by 3.\\n Step2: Add 6 with the getting result.\\n Step3: divide it by 3.\\n Step4: Subtract the first number.\\n\\n Step1: Double the second number.\\n Step2: Add 9 with result.\\n Step3: Subtract 3 with the result.\\n Step4: Divide the result by 2.\\n Step5: Subtract the result with the second number.\\n\\n Step1:Add 7 to the third number.\\n Step2:Multiply the number with 2.\\n Step3:Subtract 4 from the result.\\n Step4:Divide the result by 2.\\n Step5:Subtract the third number from the result.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn a single row matrix with the three answers.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44093,"title":"Determinants","description":"Given a square matrix(A), find the determinant(d).\r\n\r\nFor example:\r\n\r\nA = [1,3;4,5]\r\n\r\nd = 1*5-4*3 = -7","description_html":"\u003cp\u003eGiven a square matrix(A), find the determinant(d).\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cp\u003eA = [1,3;4,5]\u003c/p\u003e\u003cp\u003ed = 1*5-4*3 = -7\u003c/p\u003e","function_template":"function d = your_fcn_name(A)\r\n  d = A;\r\nend","test_suite":"%%\r\nA = [1,3;4,5];\r\nd_correct = -7;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [6,0,0,5;1,7,2,-5;2,0,0,0;8,3,1,8];\r\nd_correct = 10;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [1,0,4;2,3,2;0,5,-2];\r\nd_correct = 24;\r\nassert(isequal(your_fcn_name(A),d_correct))\r\n\r\n%%\r\nA = [4,0,-7,3,-5;0,0,2,0,0;7,3,-6,4,-8;5,0,5,2,-3;0,0,9,-1,2];\r\nd_correct = 6;\r\nassert(isequal(your_fcn_name(A),d_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":126209,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":72,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-04-13T19:49:36.000Z","updated_at":"2026-03-16T09:24:14.000Z","published_at":"2017-04-13T19:52:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a square matrix(A), find the determinant(d).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA = [1,3;4,5]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ed = 1*5-4*3 = -7\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1667,"title":"What number has this problem?","description":"This problem is added because it is problem number *???* in the \"Community\" problems section.\r\n\r\n\u003chttp://www.mathworks.de/matlabcentral/cody/?sort=\u0026term=group%3ACommunity A lots of problems here!\u003e\r\n\r\n\r\nThank you, Community!\r\n\r\nand... \r\n\r\nThank you Matlab!!","description_html":"\u003cp\u003eThis problem is added because it is problem number \u003cb\u003e???\u003c/b\u003e in the \"Community\" problems section.\u003c/p\u003e\u003cp\u003e\u003ca href = \"http://www.mathworks.de/matlabcentral/cody/?sort=\u0026term=group%3ACommunity\"\u003eA lots of problems here!\u003c/a\u003e\u003c/p\u003e\u003cp\u003eThank you, Community!\u003c/p\u003e\u003cp\u003eand...\u003c/p\u003e\u003cp\u003eThank you Matlab!!\u003c/p\u003e","function_template":"function nr = celebrating_Problem()\r\n  nr = ???;\r\nend","test_suite":"%%\r\nweCelebrateProblemNumber = 1000;\r\nassert(isequal(celebrating_Problem(),weCelebrateProblemNumber))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":2,"created_by":3038,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":405,"test_suite_updated_at":"2013-06-20T22:47:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-20T22:38:15.000Z","updated_at":"2026-05-05T18:09:22.000Z","published_at":"2013-06-20T22:47:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis problem is added because it is problem number\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e???\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e in the \\\"Community\\\" problems section.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.de/matlabcentral/cody/?sort=\u0026amp;term=group%3ACommunity\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eA lots of problems here!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThank you, Community!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThank you Matlab!!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2416,"title":"Let's see how peculiar we can get","description":"The task is to multiply two numbers. But do it in the most peculiar possible way.","description_html":"\u003cp\u003eThe task is to multiply two numbers. But do it in the most peculiar possible way.\u003c/p\u003e","function_template":"function ans = multPec(x,y)\r\n  x*y;\r\nend","test_suite":"%%\r\nassert(isequal(multPec(2,3),6))\r\n\r\nassert(isequal(multPec(2,2),4))\r\n\r\nassert(isequal(multPec(10,-10),-100))\r\n\r\nassert(isequal(multPec(.2,-.3),-.06))\r\n\r\nassert(isequal(multPec(2i,1i),-2))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":199,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-07-13T17:25:26.000Z","updated_at":"2026-02-17T14:36:31.000Z","published_at":"2014-07-13T17:26:22.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe task is to multiply two numbers. But do it in the most peculiar possible way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44444,"title":"Problem 44444 !!!  free beer everyone","description":"just say hallelujah to solve this problem","description_html":"\u003cp\u003ejust say hallelujah to solve this problem\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = 'oups'%%%\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 'hallelujah';\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":111,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-08T13:35:52.000Z","updated_at":"2026-02-20T14:19:26.000Z","published_at":"2017-12-08T13:36:00.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ejust say hallelujah to solve this problem\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1230,"title":"Who is the smartest MATLAB programmer?","description":"Who is the smartest MATLAB programmer?\r\n\r\nExamples:\r\n\r\n  Input x = 'Is it Obama?'\r\n  Output = 'Me!'\r\n\r\n  Input x = 'Who ?'\r\n  Output = 'Me!'\r\n\r\nReturn 'Me!' to all inputs. (Note: this is only a joke!)","description_html":"\u003cp\u003eWho is the smartest MATLAB programmer?\u003c/p\u003e\u003cp\u003eExamples:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eInput x = 'Is it Obama?'\r\nOutput = 'Me!'\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eInput x = 'Who ?'\r\nOutput = 'Me!'\r\n\u003c/pre\u003e\u003cp\u003eReturn 'Me!' to all inputs. (Note: this is only a joke!)\u003c/p\u003e","function_template":"function y = smartest(x)\r\n  y = 'Not me!';\r\nend","test_suite":"%%\r\nx = 'I have been using MATLAB for 50 years!';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = 'I developed MATLAB!';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = '';\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n\r\n%%\r\nx = 1;\r\ny_correct = 'Me!';\r\nassert(isequal(smartest(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":3,"created_by":10338,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":793,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-30T01:41:14.000Z","updated_at":"2026-06-19T12:49:54.000Z","published_at":"2013-01-30T01:41:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWho is the smartest MATLAB programmer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Input x = 'Is it Obama?'\\nOutput = 'Me!'\\n\\nInput x = 'Who ?'\\nOutput = 'Me!']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn 'Me!' to all inputs. (Note: this is only a joke!)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43740,"title":"Create a New_Word","description":"The output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end. ","description_html":"\u003cp\u003eThe output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end.\u003c/p\u003e","function_template":"function y = New_Word(Old_Word)\r\n  y = Old_Word;\r\nend","test_suite":"%%\r\nOld_Word = 'Welcome';\r\ny_correct = 'meelcoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Pertinacious';\r\ny_correct = 'usertinacioy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Homogenous';\r\ny_correct = 'usomogenoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Homologous';\r\ny_correct = 'usomologoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Extemperaneous';\r\ny_correct = 'usxtemperaneoy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))\r\n%%\r\nOld_Word = 'Deterministic';\r\ny_correct = 'iceterministy';\r\nassert(strcmp(New_Word(Old_Word),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":100857,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2016-12-22T18:10:34.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-07T16:56:19.000Z","updated_at":"2026-05-29T02:43:19.000Z","published_at":"2016-12-07T16:56:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output of the function is a new word created from the word entered into the function. The new word is created by deleting the first letter, taking the last 2 letters and moving them to the front, and adding y to the end.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1437,"title":"Who has power to do everything in this world?","description":"There is only one person who is older than this universe. \r\nHe is Indian version of Chuck Norris.","description_html":"\u003cp\u003eThere is only one person who is older than this universe. \r\nHe is Indian version of Chuck Norris.\u003c/p\u003e","function_template":"function y = your_fcn_name\r\n  y;\r\nend","test_suite":"%%\r\nassert(isequal(your_fcn_name,'Rajnikanth'))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":3,"created_by":10792,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":491,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-19T19:24:35.000Z","updated_at":"2026-08-21T08:12:54.000Z","published_at":"2013-04-19T19:24:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is only one person who is older than this universe. He is Indian version of Chuck Norris.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44524,"title":"Perimeter of a quadrilateral","description":"There are four cars starting at a point.  The first car points north, the second one points east, the third one points south, and the last one points west.  Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west.  After t hours, the position of the cars can be viewed as a quadrilateral from space.  Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.","description_html":"\u003cp\u003eThere are four cars starting at a point.  The first car points north, the second one points east, the third one points south, and the last one points west.  Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west.  After t hours, the position of the cars can be viewed as a quadrilateral from space.  Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.\u003c/p\u003e","function_template":"function p = total_distance(n,e,s,w,t)\r\n  p = sqrt(n*e*s*t);\r\nend","test_suite":"%%\r\nn=10;\r\ne=10;\r\ns=10;\r\nw=10;\r\nt=2;\r\ny_correct=113.1371;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n%%\r\nn=15;\r\ne=7;\r\ns=3;\r\nw=15;\r\nt=1.5;\r\ny_correct=91.0185;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n%%\r\nn=11;\r\ne=21;\r\ns=31;\r\nw=41;\r\nt=1.7;\r\ny_correct=263.5003;\r\nassert(abs(total_distance(n,e,s,w,t)-y_correct)\u003c1e-4)\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2018-02-16T18:58:53.000Z","updated_at":"2026-05-29T05:09:35.000Z","published_at":"2018-02-16T18:58:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are four cars starting at a point. The first car points north, the second one points east, the third one points south, and the last one points west. Each car moves in its respective direction at a particular speed: n km/h to the north, e km/h to the east, s km/h to the south, and w km/h to the west. After t hours, the position of the cars can be viewed as a quadrilateral from space. Determine the perimeter of this quadrilateral given the values of n, e, s, w, and t.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1681,"title":"Do you like your boss?","description":"Do you like your boss?\r\nAnswer can be any string!\r\n\r\nFor example:\r\n\r\nBoss = 'Do you like your boss?';\r\n\r\nOutput = 'yes'\r\n\r\nor \r\n\r\nBoss = 'Do you like your boss?';\r\n\r\nOutput = 'Sometimes'\r\n\r\nor\r\n\r\nBoss = 'Do you like your boss?'\r\n\r\nOutput = 'No'\r\n\r\nBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\r\n","description_html":"\u003cp\u003eDo you like your boss?\r\nAnswer can be any string!\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?';\u003c/p\u003e\u003cp\u003eOutput = 'yes'\u003c/p\u003e\u003cp\u003eor\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?';\u003c/p\u003e\u003cp\u003eOutput = 'Sometimes'\u003c/p\u003e\u003cp\u003eor\u003c/p\u003e\u003cp\u003eBoss = 'Do you like your boss?'\u003c/p\u003e\u003cp\u003eOutput = 'No'\u003c/p\u003e\u003cp\u003eBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\u003c/p\u003e","function_template":"function Answer = YourBoss(Qustion)\r\n  Answer = 'So whats the answer???';\r\nend","test_suite":"%%\r\nx = 'Do you like your boss?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Does your boss smell funny?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Is your boss a man or a woman?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Is your boss mean or nice?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Do you see your boss often?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'If your boss were an animal, what type of animal would he or she be?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'On a scale from one to ten, where does your boss rank?';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Maybe you are your own boss...';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))\r\n%%\r\nx = 'Maybe your boss is standing behind you, with that glare on his face, tapping his foot with his arms folded...';\r\ny_correct = 'Any String!';\r\nassert(isequal(isstr(YourBoss(x)),isstr(y_correct)))","published":true,"deleted":false,"likes_count":5,"comments_count":2,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":647,"test_suite_updated_at":"2013-06-27T16:47:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-27T15:50:45.000Z","updated_at":"2026-08-14T23:15:04.000Z","published_at":"2013-06-27T16:00:56.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDo you like your boss? Answer can be any string!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?';\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?';\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'Sometimes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBoss = 'Do you like your boss?'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput = 'No'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBe creative or vent (in code...) or tell how wonderful he or she is! Enjoy..\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1384,"title":"Who invented zero?","description":"We know the importance zero in computer science, mathematics... but who invented zero?\r\n\r\nClue:\r\n\r\nHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.","description_html":"\u003cp\u003eWe know the importance zero in computer science, mathematics... but who invented zero?\u003c/p\u003e\u003cp\u003eClue:\u003c/p\u003e\u003cp\u003eHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.\u003c/p\u003e","function_template":"function y = zero()\r\n  y = 'zero';\r\nend","test_suite":"%%\r\nassert(isequal(zero(),'Aryabhata'))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":4,"created_by":6975,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":612,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-25T09:04:11.000Z","updated_at":"2026-08-15T02:34:27.000Z","published_at":"2013-03-25T09:04:11.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe know the importance zero in computer science, mathematics... but who invented zero?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eClue:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHe was the first in the line of great mathematician-astronomers from the classical age of Indian mathematics and Indian astronomy.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1188,"title":"The Answer to Life, the Universe, and Everything","description":"A variation of a previous Hitchhiker's Guide to the Galaxy problem.\r\n\r\n*Inputs:* Life, the Universe, and Everything\r\n\r\n*Output:* The Answer","description_html":"\u003cp\u003eA variation of a previous Hitchhiker's Guide to the Galaxy problem.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e Life, the Universe, and Everything\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e The Answer\u003c/p\u003e","function_template":"function answer = answer_to(life,universe,everything)\r\n  answer = [];\r\nend","test_suite":"%%\r\nanswer = 42;\r\nassert(isequal(answer_to('life'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('universe'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('everything'),answer))\r\n\r\n%%\r\nanswer = 42;\r\nassert(isequal(answer_to('life','universe','everything'),answer))","published":true,"deleted":false,"likes_count":5,"comments_count":4,"created_by":1057,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":588,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-08T12:59:24.000Z","updated_at":"2026-08-28T11:45:28.000Z","published_at":"2013-01-08T12:59:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA variation of a previous Hitchhiker's Guide to the Galaxy problem.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Life, the Universe, and Everything\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e The Answer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":157,"title":"The Hitchhiker's Guide to MATLAB","description":"Output logical \"true\" if the input is the answer to life, the universe and everything. Otherwise, output logical \"false\".","description_html":"\u003cp\u003eOutput logical \"true\" if the input is the answer to life, the universe and everything. Otherwise, output logical \"false\".\u003c/p\u003e","function_template":"function y = zaphod(x)\r\n  y = false\r\nend","test_suite":"%%\r\nx = 41;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 42;\r\ny_correct = true;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 43;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 44;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 45;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 46;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))%%\r\nx = 47;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 48;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 49;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))\r\n%%\r\nx = 50;\r\ny_correct = false;\r\nassert(isequal(zaphod(x),y_correct))","published":true,"deleted":false,"likes_count":54,"comments_count":19,"created_by":39,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3426,"test_suite_updated_at":"2012-01-29T03:52:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-29T03:52:07.000Z","updated_at":"2026-08-19T06:23:07.000Z","published_at":"2012-01-29T03:53:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput logical \\\"true\\\" if the input is the answer to life, the universe and everything. Otherwise, output logical \\\"false\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":167,"title":"Pizza!","description":"Given a circular pizza with radius z and thickness a, return the pizza's volume. [ z is first input argument.]\r\nNon-scored bonus question: Why is the function interesting?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 102.5px 8px; transform-origin: 102.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a circular pizza with radius\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3.5px 8px; transform-origin: 3.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ez\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.5px 8px; transform-origin: 45.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and thickness\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ea\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 88px 8px; transform-origin: 88px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, return the pizza's volume. [\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3.5px 8px; transform-origin: 3.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ez\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 74px 8px; transform-origin: 74px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is first input argument.]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 190px 8px; transform-origin: 190px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNon-scored bonus question: Why is the function interesting?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = pizza(z,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('pizza.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'if') || contains(filetext, 'switch'); \r\nassert(~illegal)\r\n\r\n%%\r\nz = 1;\r\na = 1;\r\nv_correct = pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 2;\r\na = 1;\r\nv_correct = 4*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 1;\r\na = 2;\r\nv_correct = 2*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n\r\n%%\r\nz = 2;\r\na = 2;\r\nv_correct = 8*pi;\r\nassert(isequal(pizza(z,a),v_correct))\r\n","published":true,"deleted":false,"likes_count":377,"comments_count":316,"created_by":39,"edited_by":223089,"edited_at":"2022-12-19T07:41:42.000Z","deleted_by":null,"deleted_at":null,"solvers_count":24265,"test_suite_updated_at":"2022-12-19T07:41:42.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-29T16:17:01.000Z","updated_at":"2026-09-30T22:11:08.000Z","published_at":"2012-01-29T16:21:23.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a circular pizza with radius\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ez\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and thickness\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, return the pizza's volume. [\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ez\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is first input argument.]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNon-scored bonus question: Why is the function interesting?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":149,"title":"Is my wife right?","description":"Regardless of input, output the string 'yes'.","description_html":"\u003cp\u003eRegardless of input, output the string 'yes'.\u003c/p\u003e","function_template":"function out = wiferight(in)\r\n  out='no';\r\nend","test_suite":"%%\r\nx = 'But I''m actually right this time';\r\ny_correct = 'yes';\r\nassert(isequal(wiferight(x),y_correct))\r\n\r\n%%\r\nx = 'But you just said that 2+2=3';\r\ny_correct = 'yes';\r\nassert(isequal(wiferight(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":297,"comments_count":71,"created_by":39,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17468,"test_suite_updated_at":"2012-01-29T04:12:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-28T17:50:24.000Z","updated_at":"2026-09-27T17:44:28.000Z","published_at":"2012-01-29T04:12:44.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRegardless of input, output the string 'yes'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49962,"title":"When the sum of the squares is a cubic...","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 83.5px; transform-origin: 407px 83.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eConsider the following equality:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 65px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 32.5px; text-align: left; transform-origin: 384px 32.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"314\" height=\"59\" style=\"vertical-align: baseline;width: 314px;height: 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor a given value of n (i.e., num in the problem statement), determine the values of a's and b that satisfy the equality above. The answer should be put in a vector where the first \"num\" entries are the values of a's and the last entry is b. There is no unique answer to each of the problems; however, your answer will be checked against the requirement.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = square_cubic(num)\r\n  y = ones(num);\r\nend","test_suite":"%%\r\nnum=1;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=2;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=3;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=4;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=5;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n%%\r\nnum=6;\r\ny=square_cubic(num);\r\naa=0;\r\nfor i=1:length(y)-1\r\n    aa=aa+y(i)^2;\r\nend\r\nassert(isequal(aa,y(end)^3))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":24,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-23T22:19:52.000Z","updated_at":"2026-05-30T22:18:56.000Z","published_at":"2021-01-23T22:20:27.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider the following equality:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"59\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"314\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor a given value of n (i.e., num in the problem statement), determine the values of a's and b that satisfy the equality above. 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Pillar","description":"Calculate the volume of a pillar with radius l and heigth ar.","description_html":"\u003cp\u003eCalculate the volume of a pillar with radius l and heigth ar.\u003c/p\u003e","function_template":"function y = Pillar_Size(l,ar)\r\n  y = x;\r\nend","test_suite":"%%\r\nl = 1;\r\nar = 2;\r\ny_correct = pi*2;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))\r\n\r\n%%\r\nl = 12;\r\nar = 25;\r\ny_correct = pi*3600;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))\r\n\r\n%%\r\nl = 6;\r\nar = 2;\r\ny_correct = pi*72;\r\nassert(isequal(Pillar_Size(l,ar),y_correct))","published":true,"deleted":false,"likes_count":15,"comments_count":1,"created_by":99516,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2277,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-02-06T15:36:59.000Z","updated_at":"2026-09-30T22:25:20.000Z","published_at":"2017-02-06T15:36:59.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the volume of a pillar with radius l and heigth ar.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43571,"title":"How many hours are there in a day in Italy?","description":"Remember \"European Summer Time\"","description_html":"\u003cp\u003eRemember \"European Summer Time\"\u003c/p\u003e","function_template":"function HH = your_fcn_name(y,m,d)\r\n  HH = [y,m,d];\r\nend","test_suite":"%%\r\ny = 2016;\r\nm = 1;\r\nd = 1;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n%%\r\ny = 2016;\r\nm = 12;\r\nd = 31;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n%%\r\ny = 1965;\r\nm = 12;\r\nd = 7;\r\ny_correct = 24;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n\r\n\r\n%%\r\ny = 2016;\r\nm = 10;\r\nd = 30;\r\ny_correct = 25;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n\r\n\r\n\r\n\r\n%%\r\ny = 2016;\r\nm = 3;\r\nd = 27;\r\ny_correct = 23;\r\nassert(isequal(your_fcn_name(y,m,d),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":14644,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-17T14:33:18.000Z","updated_at":"2026-05-29T01:44:44.000Z","published_at":"2016-10-17T14:36:36.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember \\\"European Summer Time\\\"\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1561,"title":"Reverse CHECKBOX MATRIX with 69","description":"Create a reverse checkbox matrix with '69'.   \r\nWhere the size is the input and output will be a square checkbox matrix. \r\n\r\nExample\r\n\r\nIf input is 4 then output will be \r\n\r\n    [ 0    69     0    69 \r\n     69     0    69     0 \r\n      0    69     0    69 \r\n     69     0    69     0]\r\n","description_html":"\u003cp\u003eCreate a reverse checkbox matrix with '69'.   \r\nWhere the size is the input and output will be a square checkbox matrix.\u003c/p\u003e\u003cp\u003eExample\u003c/p\u003e\u003cp\u003eIf input is 4 then output will be\u003c/p\u003e\u003cpre\u003e    [ 0    69     0    69 \r\n     69     0    69     0 \r\n      0    69     0    69 \r\n     69     0    69     0]\u003c/pre\u003e","function_template":"function y = ChecK69(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 3;\r\ny_correct = [0 69 0;69 0 69;0 69 0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 4;\r\ny_correct = [0    69     0    69;\r\n            69     0    69     0;\r\n             0    69     0    69;\r\n            69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 5;\r\ny_correct =[0    69     0    69     0;\r\n           69     0    69     0    69;\r\n            0    69     0    69     0;\r\n           69     0    69     0    69;\r\n            0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 6;\r\ny_correct =[0    69     0    69     0    69;\r\n           69     0    69     0    69     0;\r\n            0    69     0    69     0    69;\r\n           69     0    69     0    69     0;\r\n            0    69     0    69     0    69;\r\n           69     0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))\r\n\r\n%%\r\nx = 8;\r\ny_correct =[0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0;\r\n            0    69     0    69     0    69     0    69;\r\n           69     0    69     0    69     0    69     0];\r\nassert(isequal(ChecK69(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":13514,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":86,"test_suite_updated_at":"2013-06-06T11:31:41.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-06T11:26:14.000Z","updated_at":"2026-03-05T16:34:45.000Z","published_at":"2013-06-06T11:26:18.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCreate a reverse checkbox matrix with '69'. Where the size is the input and output will be a square checkbox matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is 4 then output will be\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    [ 0    69     0    69 \\n     69     0    69     0 \\n      0    69     0    69 \\n     69     0    69     0]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1719,"title":"Dice face matrix!","description":"This is dice simulator, but instead of making a random die number, you will receive an \"pre-rolled\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\r\n\r\n  rollnum = 1;\r\n\r\nThen the output will be:\r\n\r\n  diceFace =\r\n  \r\n       0     0     0\r\n       0     1     0\r\n       0     0     0\r\n\r\nAnother example:\r\n\r\n  rollnum = 5;\r\n\r\nThen the output will be:\r\n\r\n  diceFace =\r\n  \r\n       1     0     1\r\n       0     1     0\r\n       1     0     1\r\nAnd so on for 1-6, well that is it!\r\nJust note the 1 and 0 are numbers not char's or strings...\r\nGood luck!","description_html":"\u003cp\u003eThis is dice simulator, but instead of making a random die number, you will receive an \"pre-rolled\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003erollnum = 1;\r\n\u003c/pre\u003e\u003cp\u003eThen the output will be:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ediceFace =\r\n\u003c/pre\u003e\u003cpre\u003e       0     0     0\r\n       0     1     0\r\n       0     0     0\u003c/pre\u003e\u003cp\u003eAnother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003erollnum = 5;\r\n\u003c/pre\u003e\u003cp\u003eThen the output will be:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ediceFace =\r\n\u003c/pre\u003e\u003cpre\u003e       1     0     1\r\n       0     1     0\r\n       1     0     1\r\nAnd so on for 1-6, well that is it!\r\nJust note the 1 and 0 are numbers not char's or strings...\r\nGood luck!\u003c/pre\u003e","function_template":"function diceFace = rollADie(rollnum)\r\n  diceFace = rollnum;\r\nend","test_suite":"%%\r\nrollnum = 1;\r\ndiceFace = [0 0 0; 0 1 0; 0 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 2;\r\ndiceFace = [0 0 1; 0 0 0; 1 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 3;\r\ndiceFace = [0 0 1; 0 1 0; 1 0 0];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 4;\r\ndiceFace = [1 0 1; 0 0 0; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 5;\r\ndiceFace = [1 0 1; 0 1 0; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n%%\r\nrollnum = 6;\r\ndiceFace = [1 0 1; 1 0 1; 1 0 1];\r\nassert(isequal(rollADie(rollnum),diceFace))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":139,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":41,"created_at":"2013-07-16T15:48:23.000Z","updated_at":"2026-09-03T10:57:51.000Z","published_at":"2013-07-16T15:48:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is dice simulator, but instead of making a random die number, you will receive an \\\"pre-rolled\\\" number in and spit out a matrix of 1 and 0 that looks like a dice face of the given number. So for example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[rollnum = 1;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen the output will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[diceFace =\\n\\n       0     0     0\\n       0     1     0\\n       0     0     0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnother example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[rollnum = 5;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen the output will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[diceFace =\\n\\n       1     0     1\\n       0     1     0\\n       1     0     1\\nAnd so on for 1-6, well that is it!\\nJust note the 1 and 0 are numbers not char's or strings...\\nGood luck!]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1712,"title":"NO _________ ALLOWED....","description":"So you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0.  For example:\r\n\r\n  Sentence = 'The birds in the field are eating bird seed';\r\n  Not_allowed = 'field'\r\n\r\nso the output will be, because field is found in the sentence:\r\n\r\n  Output = 1; \r\n\r\nAnother example:\r\n\r\n  Sentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\n  Not_allowed = 'oven'\r\n\r\nso the output will be, because oven is not found in the sentence:\r\n\r\n  Output = 0; \r\n\r\nThat is it!\r\n\r\nHave Fun!","description_html":"\u003cp\u003eSo you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0.  For example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eSentence = 'The birds in the field are eating bird seed';\r\nNot_allowed = 'field'\r\n\u003c/pre\u003e\u003cp\u003eso the output will be, because field is found in the sentence:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput = 1; \r\n\u003c/pre\u003e\u003cp\u003eAnother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eSentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\nNot_allowed = 'oven'\r\n\u003c/pre\u003e\u003cp\u003eso the output will be, because oven is not found in the sentence:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput = 0; \r\n\u003c/pre\u003e\u003cp\u003eThat is it!\u003c/p\u003e\u003cp\u003eHave Fun!\u003c/p\u003e","function_template":"function output = NotAllowed(Sentence, Not_allowed)\r\n  output = Not_allowed;\r\n  output = Sentence;\r\nend","test_suite":"%%\r\nSentence = 'The birds in the field are eating bird seed';\r\nNot_allowed = 'field'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'If the sky is blue on earth, what is the sky color on mars?';\r\nNot_allowed = 'oven'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Oh where, oh where has my little dog gone?';\r\nNot_allowed = 'where'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Insanity: doing the same thing over and over again and expecting different results...';\r\nNot_allowed = 'Einstein'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'Wheres the cream filling?';\r\nNot_allowed = 'cream'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'MATLAB is the coolest!';\r\nNot_allowed = 'MATLAB'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'No no, you got it all wrong!';\r\nNot_allowed = 'No'\r\noutput = 1;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))\r\n%%\r\nSentence = 'This planet, with all its appalling immensity, is to electric currents virtually no more than a small metal ball.';\r\nNot_allowed = 'Tesla'\r\noutput = 0;\r\nassert(isequal(NotAllowed(Sentence, Not_allowed),output))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":232,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-12T16:08:38.000Z","updated_at":"2026-05-12T20:49:10.000Z","published_at":"2013-07-12T16:08:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo you're given a sentence where if there is a particular word in the sentence then the output is 1, if it is not there then the output is 0. For example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Sentence = 'The birds in the field are eating bird seed';\\nNot_allowed = 'field']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the output will be, because field is found in the sentence:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Output = 1;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnother example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Sentence = 'If the sky is blue on earth, what is the sky color on mars?';\\nNot_allowed = 'oven']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the output will be, because oven is not found in the sentence:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[Output = 0;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThat is it!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHave Fun!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42766,"title":"Is my wife really right?","description":"For every input, output the string 'yes' once.\r\nExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\r\nyes1 = 'yes'\r\nyes2 = 'yes'","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 111px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 55.5px; transform-origin: 407px 55.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 139px 8px; transform-origin: 139px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor every input, output the string 'yes' once.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 207px 8px; transform-origin: 207px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 37px 8px; transform-origin: 37px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyes1 = 'yes'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 37px 8px; transform-origin: 37px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyes2 = 'yes'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function yes = YesSheIs('?')\r\n  y = 'no';\r\nend","test_suite":"%%\r\nQuestion1 = 'Will you be ready soon?';\r\nQuestion2 = 'What is the meaning of life, universe and everything?';\r\nQuestion3 = 'Do you wan''t to go out today?';\r\nQuestion4 = 'Can you help me?';\r\ny_correct = ['yes', 'yes', 'yes', 'yes'];\r\n[yes1, yes2, yes3, yes4] = YesSheIs(Question1, Question2, Question3, Question4);\r\nassert(strcmp([yes1, yes2, yes3, yes4] ,y_correct))\r\n\r\n\r\n%% \r\nQuestion1 = 'Will you be ready soon?';\r\nQuestion2 = 'What is the meaning of life, universe and everything?';\r\nQuestion3 = 'Do you wan''t to go out today?';\r\nQuestion4 = 'Can you help me?';\r\ny_correct = ['yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes'];\r\n[yes1, yes2, yes3, yes4, yes5, yes6, yes7, yes8, yes9] = YesSheIs(Question1, Question2, Question3, Question4, Question1, Question2, Question3, Question4, Question3);\r\nassert(strcmp([yes1, yes2, yes3, yes4, yes5, yes6, yes7, yes8, yes9] , y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":68531,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":38,"test_suite_updated_at":"2021-09-05T10:31:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-03-07T17:01:12.000Z","updated_at":"2026-07-10T09:48:00.000Z","published_at":"2016-03-07T17:01:16.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor every input, output the string 'yes' once.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: [yes1, yes2] = YesSheIs('Am I right?', 'Do you love me?')\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eyes1 = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eyes2 = 'yes'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1630,"title":"~~~~~~~ WAVE ~~~~~~~~~","description":"|The WAVE generator|\r\n\r\nOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone. \r\n\r\n|For EXAMPLE|: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\r\n\r\n     1     1     1     1     1     1\r\n     1     2     2     2     2     2\r\n     1     2     3     3     3     3\r\n     1     2     3     4     4     4\r\n     1     2     3     4     5     5\r\n     1     2     3     4     5     6","description_html":"\u003cp\u003e\u003ctt\u003eThe WAVE generator\u003c/tt\u003e\u003c/p\u003e\u003cp\u003eOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone.\u003c/p\u003e\u003cp\u003e\u003ctt\u003eFor EXAMPLE\u003c/tt\u003e: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\u003c/p\u003e\u003cpre\u003e     1     1     1     1     1     1\r\n     1     2     2     2     2     2\r\n     1     2     3     3     3     3\r\n     1     2     3     4     4     4\r\n     1     2     3     4     5     5\r\n     1     2     3     4     5     6\u003c/pre\u003e","function_template":"function waves = WAVE(stone)\r\n  waves = stone;\r\nend","test_suite":"%%\r\nstone = 2;\r\nwaves =[1     1;\r\n        1     2];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 3;\r\nwaves =    [1     1     1;\r\n            1     2     2;\r\n            1     2     3];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 4;\r\nwaves =    [     1     1     1     1;\r\n                 1     2     2     2;\r\n                 1     2     3     3;\r\n                 1     2     3     4;];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 6;\r\nwaves =    [ 1     1     1     1     1     1;\r\n             1     2     2     2     2     2;\r\n             1     2     3     3     3     3;\r\n             1     2     3     4     4     4;\r\n             1     2     3     4     5     5;\r\n             1     2     3     4     5     6];\r\nassert(isequal( WAVE(stone),waves))\r\n\r\n%%\r\nstone = 10;\r\nwaves =    [   1     1     1     1     1     1     1     1     1     1;\r\n     1     2     2     2     2     2     2     2     2     2;\r\n     1     2     3     3     3     3     3     3     3     3;\r\n     1     2     3     4     4     4     4     4     4     4;\r\n     1     2     3     4     5     5     5     5     5     5;\r\n     1     2     3     4     5     6     6     6     6     6;\r\n     1     2     3     4     5     6     7     7     7     7;\r\n     1     2     3     4     5     6     7     8     8     8;\r\n     1     2     3     4     5     6     7     8     9     9;\r\n     1     2     3     4     5     6     7     8     9    10];\r\nassert(isequal( WAVE(stone),waves))","published":true,"deleted":false,"likes_count":15,"comments_count":2,"created_by":13514,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":349,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-06-07T09:32:28.000Z","updated_at":"2026-07-10T13:49:21.000Z","published_at":"2013-06-07T09:32:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eThe WAVE generator\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce upon a time there was a river. 'Sum' was passing by the river. He saw the water of the river that was so still and clear as crystal. He threw a stone into river. Then again he threw another stone of higher weight into the river.He saw there was two different kinds of waves were being generated due to the difference in weight of the stone.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFor EXAMPLE\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: 'Sum' threw a stone of weight 6. The river generated wave as bellow.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[     1     1     1     1     1     1\\n     1     2     2     2     2     2\\n     1     2     3     3     3     3\\n     1     2     3     4     4     4\\n     1     2     3     4     5     5\\n     1     2     3     4     5     6]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1062,"title":"Three grind is shipsstraigt","description":"A function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests. ","description_html":"\u003cp\u003eA function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests.\u003c/p\u003e","function_template":"function y = driemaalisscheepsrecht()\r\n  y = 'Zizzors';\r\nend","test_suite":"%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));\r\n\r\n%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));\r\n\r\n%%\r\ny_correct = getfield({'rock' 'scissors' 'paper'},{ceil(rand(1)*3)});\r\nassert(isequal(lower(driemaalisscheepsrecht()),y_correct));","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":47,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-26T11:32:14.000Z","updated_at":"2026-07-20T10:44:23.000Z","published_at":"2012-11-26T11:39:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA function that returns either 'Rock', 'Scissors', or 'Paper' (string). You may succeed or you may fail the (case insensitive) tests.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1052,"title":"Elapsed time is -0.005204 seconds.","description":"Write a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\r\n\r\n  tic\r\n  pause(1)\r\n  superfast()\r\n  toc\r\n\r\n  Elapsed time is 0.9876 seconds.","description_html":"\u003cp\u003eWrite a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003etic\r\npause(1)\r\nsuperfast()\r\ntoc\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eElapsed time is 0.9876 seconds.\r\n\u003c/pre\u003e","function_template":"function y = superfast(x)\r\n  pause(-1)\r\nend","test_suite":"%%\r\ntic\r\npause(1)\r\nsuperfast()\r\ntimeElapsed = toc;\r\nassert(timeElapsed \u003c 1)\r\n","published":true,"deleted":false,"likes_count":7,"comments_count":1,"created_by":450,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":105,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-11-23T21:59:46.000Z","updated_at":"2026-07-10T09:26:19.000Z","published_at":"2012-11-23T22:07:28.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes less than zero seconds to execute, as measured using tic and toc. For repeatability, the test case pauses for one second. Overall time elapsed for the test case should therefore be less than one second.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[tic\\npause(1)\\nsuperfast()\\ntoc\\n\\nElapsed time is 0.9876 seconds.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43061,"title":"Chicken Race","description":"2 chickens, Pete and Fred, compete in a 100 meter race.\r\nPete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second.\r\nHowever, Fred cheats and starts before the starting shot, giving him an N seconds head start.\r\n\r\nWho wins the race? Answer 'Fred' or 'Pete'.","description_html":"\u003cp\u003e2 chickens, Pete and Fred, compete in a 100 meter race.\r\nPete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second.\r\nHowever, Fred cheats and starts before the starting shot, giving him an N seconds head start.\u003c/p\u003e\u003cp\u003eWho wins the race? Answer 'Fred' or 'Pete'.\u003c/p\u003e","function_template":"function winner = chickenRace(vf,vp,N)\r\n  winner = '???';\r\nend","test_suite":"%%%%\r\nvf = 5.5;\r\nvp = 6;\r\nN = 1;\r\nwinner = 'Pete';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n%%\r\nvf = 5.5;\r\nvp = 6;\r\nN = 2;\r\nwinner = 'Fred';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n%%\r\nvf = 6;\r\nvp = 6;\r\nN = 2;\r\nwinner = 'Fred';\r\nassert(isequal(chickenRace(vf,vp,N),winner))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":68,"test_suite_updated_at":"2016-10-19T11:44:40.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T14:26:25.000Z","updated_at":"2026-07-10T12:22:07.000Z","published_at":"2016-10-05T14:26:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e2 chickens, Pete and Fred, compete in a 100 meter race. Pete runs at a velocity of vp meter/second and Fred is slower, running at vf meter/second. However, Fred cheats and starts before the starting shot, giving him an N seconds head start.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWho wins the race? Answer 'Fred' or 'Pete'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2151,"title":"Reverse within string ","description":"If input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\r\n\r\nIf the length of the string is odd, leave the middle letter unchanged.\r\n\r\nInput 'letter' output 'telret'\r\n\r\nInput 'apple' output 'papel'","description_html":"\u003cp\u003eIf input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\u003c/p\u003e\u003cp\u003eIf the length of the string is odd, leave the middle letter unchanged.\u003c/p\u003e\u003cp\u003eInput 'letter' output 'telret'\u003c/p\u003e\u003cp\u003eInput 'apple' output 'papel'\u003c/p\u003e","function_template":"function y = reverse_within_string(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 'Help';\r\ny_correct = 'eHpl';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'between';\r\ny_correct = 'tebwnee';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'yellow';\r\ny_correct = 'leywol';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'apple';\r\ny_correct = 'papel';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'one, two, three';\r\ny_correct = 'wt ,enooeerht ,';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'red green blue';\r\ny_correct = 'erg dereulb ne';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = 'a';\r\ny_correct = 'a';\r\nassert(isequal(reverse_within_string(x),y_correct))\r\n\r\n%%\r\nx = '1234567890';\r\ny_correct = '5432109876';\r\nassert(isequal(reverse_within_string(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":22585,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":160,"test_suite_updated_at":"2017-09-27T15:43:07.000Z","rescore_all_solutions":false,"group_id":32,"created_at":"2014-02-05T10:25:53.000Z","updated_at":"2026-08-13T22:26:59.000Z","published_at":"2014-02-05T10:27:40.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is a string 'yellow' the output should be 'leywol'. Locate the middle of the string and reverse the first (yel) and second (low)parts of the string.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the length of the string is odd, leave the middle letter unchanged.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput 'letter' output 'telret'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput 'apple' output 'papel'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44441,"title":"Jack's hand in \"Titanic\" ♤","description":"Given a series of cards, return true if it's the famous hand. Note that i pretend that  poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?","description_html":"\u003cp\u003eGiven a series of cards, return true if it's the famous hand. Note that i pretend that  poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m'); \r\nassert(isempty(strfind(filetext, 'regexp')),'regexp() and its family are forbidden') \r\nassert(isempty(strfind(filetext, 'regexprep')),'regexprep() forbidden')\r\n%%\r\nx = [10 3 10 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 8 1 7 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [10 5 10 5 10];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [4 4 6 3 5];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [2 4 2 4 4];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 9 9 9 9];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 7 8 7 8];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [nan 3 10 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [10 'k' 'j' 2 3];\r\ny_correct = false;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 7 8 0 8];\r\ny_correct = false; %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 17 8 17 8] ;\r\ny_correct = false %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [0 7 0 7 0];\r\ny_correct = false; %inexistant card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 3 3 8 3];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [8 .3 .3 8 .3];\r\ny_correct = false;  %invalid card\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 1 1 5 5];\r\ny_correct = true;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":"2017-12-09T11:50:03.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-06T14:41:25.000Z","updated_at":"2026-07-13T07:49:27.000Z","published_at":"2017-12-06T14:41:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a series of cards, return true if it's the famous hand. Note that i pretend that poker cards goes from 1 to 10 so be careful with the test suite to avoid some traps like (nan, 0.05 , 'string', 55...) are invalid cards right ?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2002,"title":"Schrödinger dog","description":"Everyone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all? \r\n\r\nYES! NOW IT IS!\r\n\r\nYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet. ","description_html":"\u003cp\u003eEveryone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all?\u003c/p\u003e\u003cp\u003eYES! NOW IT IS!\u003c/p\u003e\u003cp\u003eYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet.\u003c/p\u003e","function_template":"function woof = dog\r\n  woof = true;\r\nend","test_suite":"%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = true;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = false;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 42;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = pi;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 'pie';\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = true;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 0;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = -1;\r\nassert(isequal(dog,y_correct))\r\n\r\n%%\r\ny_correct = 'woof';\r\nassert(isequal(dog('what is your name?'),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":"2013-11-16T23:37:42.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-16T23:29:45.000Z","updated_at":"2026-07-10T09:33:08.000Z","published_at":"2013-11-16T23:37:42.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEveryone knows that dogs are less unpredictable than cats. But is that proven? Is that measurable at all?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYES! NOW IT IS!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are going to write a function that resembles the box with Schrödinger's dog inside, and I am going to test if it is indeed his canid pet.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":45172,"title":"Cross (\"+\") flag returns","description":"Given two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\r\nGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of two numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\r\nFor example, [m, n] = [3, 3] would return:\r\n[0,1,0;\r\n1,1,1;\r\n0,1,0];\r\nAnd for even numbers: [p, q] = [4, 3] would return\r\n[0,1,0;\r\n1,1,1;\r\n1,1,1;\r\n0,1,0];","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 317.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 158.517px; transform-origin: 407px 158.517px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383px 8px; transform-origin: 383px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 279.5px 8px; transform-origin: 279.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12.5px 8px; transform-origin: 12.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 90px 8px; transform-origin: 90px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 127.5px 8px; transform-origin: 127.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, [m, n] = [3, 3] would return:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 30.65px; transform-origin: 404px 30.65px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[0,1,0;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0,1,0];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 155px 8px; transform-origin: 155px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAnd for even numbers: [p, q] = [4, 3] would return\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[0,1,0;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 24px 8.5px; tab-size: 4; transform-origin: 24px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1,1,1;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 28px 8.5px; tab-size: 4; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0,1,0];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = crossFlag2(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 2; n = 2;\r\ny_correct = zeros(2,2);\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 3; n = 3;\r\ny_correct = [0, 1, 0; 1, 1, 1; 0, 1, 0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 4; n = 4;\r\ny_correct = [0,1,1,0;\r\n             1,1,1,1;\r\n             1,1,1,1;\r\n             0,1,1,0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 5; n = 3;\r\ny_correct = [0, 1, 0; 0, 1, 0; 1, 1, 1; 0, 1, 0; 0, 1, 0];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 3; n = 1;\r\ny_correct = ones(m,n);\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 16; n = 8;\r\ny_correct = [zeros(7,3),ones(7,2),zeros(7,3);ones(2,8);zeros(7,3),ones(7,2),zeros(7,3)];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 7; n = 280;\r\ny_correct = [zeros(3,139), ones(3,2), zeros(3,139); ones(1,280); zeros(3,139), ones(3,2), zeros(3,139)];\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 1; n = 1;\r\ny_correct = 1;\r\nassert(isequal(crossFlag2(m, n),y_correct))\r\n\r\n%%\r\nm = 0; n = 0;\r\ny_correct =[];\r\nassert(isequal(crossFlag2(m, n),y_correct));\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":8,"created_by":157354,"edited_by":223089,"edited_at":"2022-11-25T07:01:15.000Z","deleted_by":null,"deleted_at":null,"solvers_count":20,"test_suite_updated_at":"2022-11-25T07:01:15.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-11T20:16:53.000Z","updated_at":"2026-07-13T13:42:41.000Z","published_at":"2019-10-11T20:16:53.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two numbers, [m, n], return a matrix of size m x n which has all elements of the centre column and centre row set as 1, and all other elements in the matrix set as 0.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two even numbers, [p, q], return a matrix of size p x q which has the centre band of\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etwo\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e numbers set as 1. However, there must be at least four zeros on the outer corners of the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, [m, n] = [3, 3] would return:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[[0,1,0;\\n1,1,1;\\n0,1,0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd for even numbers: [p, q] = [4, 3] would return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[[0,1,0;\\n1,1,1;\\n1,1,1;\\n0,1,0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1713,"title":"Can you beat the lottery?","description":"Well this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\r\n\r\n    check = 1;\r\n    while check == 1\r\n        D1 = round(rand(1,1)*5+1);\r\n        D2 = round(rand(1,1)*5+1);\r\n        D3 = round(rand(1,1)*5+1);\r\n        draw = sort([D1 D2 D3]);\r\n        if size(unique(fn), 2) == 3\r\n            check = 0;\r\n        end\r\n    end\r\n\r\nSo \"draw\" is the draw that is made. It is made up of 3 numbers between 1 and 5.  Note that the numbers do not repeat.  SO an example of an input is:\r\n\r\nlottery = [4 3 5];\r\n\r\nNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...) \r\n\r\nGood luck, and please play responsibly...","description_html":"\u003cp\u003eWell this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\u003c/p\u003e\u003cpre\u003e    check = 1;\r\n    while check == 1\r\n        D1 = round(rand(1,1)*5+1);\r\n        D2 = round(rand(1,1)*5+1);\r\n        D3 = round(rand(1,1)*5+1);\r\n        draw = sort([D1 D2 D3]);\r\n        if size(unique(fn), 2) == 3\r\n            check = 0;\r\n        end\r\n    end\u003c/pre\u003e\u003cp\u003eSo \"draw\" is the draw that is made. It is made up of 3 numbers between 1 and 5.  Note that the numbers do not repeat.  SO an example of an input is:\u003c/p\u003e\u003cp\u003elottery = [4 3 5];\u003c/p\u003e\u003cp\u003eNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...)\u003c/p\u003e\u003cp\u003eGood luck, and please play responsibly...\u003c/p\u003e","function_template":"function draw = lottery()\r\n  draw = [x x x];\r\nend","test_suite":"%%\r\ncheck = 1;\r\nwhile check == 1\r\n     D1 = round(rand(1,1)*4+1);\r\n     D2 = round(rand(1,1)*4+1);\r\n     D3 = round(rand(1,1)*4+1);\r\n     draw = sort([D1 D2 D3]);\r\n        if size(unique(draw), 2) == 3\r\n            check = 0;\r\n        end\r\nend\r\nassert(isequal(sort(lottery()),draw))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":48,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-12T21:15:43.000Z","updated_at":"2025-11-17T20:59:24.000Z","published_at":"2013-07-12T22:07:45.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell this one you may not get every time, but it is a lottery! Here is the code that generates the lottery numbers (you can try to use it to your advantage if you can):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    check = 1;\\n    while check == 1\\n        D1 = round(rand(1,1)*5+1);\\n        D2 = round(rand(1,1)*5+1);\\n        D3 = round(rand(1,1)*5+1);\\n        draw = sort([D1 D2 D3]);\\n        if size(unique(fn), 2) == 3\\n            check = 0;\\n        end\\n    end]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo \\\"draw\\\" is the draw that is made. It is made up of 3 numbers between 1 and 5. Note that the numbers do not repeat. SO an example of an input is:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003elottery = [4 3 5];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNow the odds are 1 in 10 (or at least that is the total combinations that can occur), so if you get it exactly you win! (you win the correct answer...)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGood luck, and please play responsibly...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1687,"title":"Poker Card Deal!","description":"Anyone want to play a card game?  \r\n\r\nWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards.  Rows are the amount of people in play, columns are the amount of cards dealt to each person.  The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\r\n\r\nThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J.  The suits are s for spades, d for dimonds, h for hearts and c for clubs.  \r\n\r\nSo the final cards look like this:\r\n\r\n'js'\r\n\r\n'J'\r\n\r\n'2h'\r\n\r\n'ad'\r\n\r\n'5c' and so on.\r\n\r\nThis function reads in three variables, these are:\r\n\r\npeople -- This is the amount of people that the cards are being dealt to.\r\n\r\ncardsDelt  -- This is the amount of cards dealt to each person.\r\n\r\nisJokerIn --  This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\r\n\r\nso an example is the following, if the variables are:\r\n\r\n%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\r\n\r\npeople = 5;\r\n\r\ncardsDelt = 5; %note, this is a typical deal for a poker game...\r\n\r\nisJokerIn = 0; \r\n\r\nThe outputs will be:\r\n\r\ndealtDeck = \r\n\r\n    'qh'    'as'    '5s'     '2s'    'jd' \r\n    'ad'    '5d'    '9s'     '7h'    'ah' \r\n    '3c'    '2d'    'ac'     '8c'    'qd' \r\n    'kh'    '5h'    '4c'     '3h'    '10s'\r\n    '6h'    '8h'    '10c'    '4s'    '8d' \r\n\r\n%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\r\n\r\ndeckLeftover = \r\n\r\n    '3s'\r\n    '4h'\r\n    '2c'\r\n    '5c'\r\n    'qs'\r\n    'jh'\r\n    'kd'\r\n    '2h'\r\n    '9c'\r\n    '10h'\r\n    '9h'\r\n    '6d'\r\n    '7c'\r\n    '7s'\r\n    '8s'\r\n    'qc'\r\n    'js'\r\n    '9d'\r\n    '7d'\r\n    'ks'\r\n    '6c'\r\n    '6s'\r\n    '3d'\r\n    '10d'\r\n    'jc'\r\n    '4d'\r\n    'kc'\r\n\r\nWell I hope that everyone has fun with it!  Thank you!\r\n\r\n","description_html":"\u003cp\u003eAnyone want to play a card game?\u003c/p\u003e\u003cp\u003eWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards.  Rows are the amount of people in play, columns are the amount of cards dealt to each person.  The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\u003c/p\u003e\u003cp\u003eThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J.  The suits are s for spades, d for dimonds, h for hearts and c for clubs.\u003c/p\u003e\u003cp\u003eSo the final cards look like this:\u003c/p\u003e\u003cp\u003e'js'\u003c/p\u003e\u003cp\u003e'J'\u003c/p\u003e\u003cp\u003e'2h'\u003c/p\u003e\u003cp\u003e'ad'\u003c/p\u003e\u003cp\u003e'5c' and so on.\u003c/p\u003e\u003cp\u003eThis function reads in three variables, these are:\u003c/p\u003e\u003cp\u003epeople -- This is the amount of people that the cards are being dealt to.\u003c/p\u003e\u003cp\u003ecardsDelt  -- This is the amount of cards dealt to each person.\u003c/p\u003e\u003cp\u003eisJokerIn --  This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\u003c/p\u003e\u003cp\u003eso an example is the following, if the variables are:\u003c/p\u003e\u003cp\u003e%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\u003c/p\u003e\u003cp\u003epeople = 5;\u003c/p\u003e\u003cp\u003ecardsDelt = 5; %note, this is a typical deal for a poker game...\u003c/p\u003e\u003cp\u003eisJokerIn = 0;\u003c/p\u003e\u003cp\u003eThe outputs will be:\u003c/p\u003e\u003cp\u003edealtDeck =\u003c/p\u003e\u003cpre\u003e    'qh'    'as'    '5s'     '2s'    'jd' \r\n    'ad'    '5d'    '9s'     '7h'    'ah' \r\n    '3c'    '2d'    'ac'     '8c'    'qd' \r\n    'kh'    '5h'    '4c'     '3h'    '10s'\r\n    '6h'    '8h'    '10c'    '4s'    '8d' \u003c/pre\u003e\u003cp\u003e%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\u003c/p\u003e\u003cp\u003edeckLeftover =\u003c/p\u003e\u003cpre\u003e    '3s'\r\n    '4h'\r\n    '2c'\r\n    '5c'\r\n    'qs'\r\n    'jh'\r\n    'kd'\r\n    '2h'\r\n    '9c'\r\n    '10h'\r\n    '9h'\r\n    '6d'\r\n    '7c'\r\n    '7s'\r\n    '8s'\r\n    'qc'\r\n    'js'\r\n    '9d'\r\n    '7d'\r\n    'ks'\r\n    '6c'\r\n    '6s'\r\n    '3d'\r\n    '10d'\r\n    'jc'\r\n    '4d'\r\n    'kc'\u003c/pre\u003e\u003cp\u003eWell I hope that everyone has fun with it!  Thank you!\u003c/p\u003e","function_template":"function [dealtDeck, deckLeftover] = Poker_Deal(people,cardsDelt,isJokerIn)\r\ndealtDeck ='this is the dealt deck to players'\r\ndeckLeftover = 'is the left over cards in the deck, after being delt'\r\nend","test_suite":"%%\r\npeople = 5;\r\ncardsDelt = 5;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 25) \u0026 ~issorted(reshape(dealtDeck,25,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-25)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 5;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 15) \u0026 ~issorted(reshape(dealtDeck,15,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-15)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 4;\r\ncardsDelt = 7;\r\nisJokerIn = 0;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 28) \u0026 ~issorted(reshape(dealtDeck,28,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (52-28)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 5;\r\ncardsDelt = 6;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'; 'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 30) \u0026 ~issorted(reshape(dealtDeck,30,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-30)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 4;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac'; 'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 12) \u0026 ~issorted(reshape(dealtDeck,12,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-12)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n%%\r\npeople = 3;\r\ncardsDelt = 3;\r\nisJokerIn = 1;\r\n[dealtDeck, deckLeftover] = Poker_Deal(people ,cardsDelt ,isJokerIn)\r\ndeckCheck = {'2h'; '3h'; '4h'; '5h'; '6h'; '7h'; '8h'; '9h'; '10h'; 'jh'; 'qh'; 'kh'; 'ah'; '2d'; '3d'; '4d'; '5d'; '6d'; '7d'; '8d'; '9d'; '10d'; 'jd'; 'qd'; 'kd'; 'ad'; '2s'; '3s'; '4s'; '5s'; '6s'; '7s'; '8s'; '9s'; '10s'; 'js'; 'qs'; 'ks'; 'as'; '2c'; '3c'; '4c'; '5c'; '6c'; '7c'; '8c'; '9c'; '10c'; 'jc'; 'qc'; 'kc'; 'ac';  'J'; 'J'}\r\nh = (sum(sum(ismember(deckCheck,dealtDeck))) == 9) \u0026 ~issorted(reshape(dealtDeck,9,1));\r\ng = (sum(ismember(deckCheck,deckLeftover)) == (54-9)) \u0026 ~issorted(deckLeftover);\r\ny_correct = g\u0026h;\r\nassert(isequal(g,h))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":15,"created_at":"2013-06-30T01:06:43.000Z","updated_at":"2026-08-12T15:56:02.000Z","published_at":"2013-06-30T01:06:43.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnyone want to play a card game?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell this is making one deck of cards, with the option of using 2 jokers. The outputs are a matrix that represents dealt cards. Rows are the amount of people in play, columns are the amount of cards dealt to each person. The deck that is left over is where the cards were drawn from and is returned as well. That is it! No other things needed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe cards are named with there face value, such as 2,3,4,5,6,7,8,9,10,j,q,k,a and a joker of only the capital letter J. The suits are s for spades, d for dimonds, h for hearts and c for clubs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo the final cards look like this:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'js'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'J'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'2h'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'ad'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'5c' and so on.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis function reads in three variables, these are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003epeople -- This is the amount of people that the cards are being dealt to.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ecardsDelt -- This is the amount of cards dealt to each person.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eisJokerIn -- This is a true/false (that is 1 or 0), where 1 means 2 jokers (J) are included in play or 0 is no jokers are included in play.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso an example is the following, if the variables are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e%note this example is RANDOM, the outputs must be random to simulate a shuffled deck!!!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003epeople = 5;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ecardsDelt = 5; %note, this is a typical deal for a poker game...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eisJokerIn = 0;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe outputs will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003edealtDeck =\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    'qh'    'as'    '5s'     '2s'    'jd' \\n    'ad'    '5d'    '9s'     '7h'    'ah' \\n    '3c'    '2d'    'ac'     '8c'    'qd' \\n    'kh'    '5h'    '4c'     '3h'    '10s'\\n    '6h'    '8h'    '10c'    '4s'    '8d']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e%note, 5x5, where rows is amount of people and columns are amount of cards dealt...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003edeckLeftover =\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    '3s'\\n    '4h'\\n    '2c'\\n    '5c'\\n    'qs'\\n    'jh'\\n    'kd'\\n    '2h'\\n    '9c'\\n    '10h'\\n    '9h'\\n    '6d'\\n    '7c'\\n    '7s'\\n    '8s'\\n    'qc'\\n    'js'\\n    '9d'\\n    '7d'\\n    'ks'\\n    '6c'\\n    '6s'\\n    '3d'\\n    '10d'\\n    'jc'\\n    '4d'\\n    'kc']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWell I hope that everyone has fun with it! Thank you!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2459,"title":"grazing cows","description":"Here is a fun problem I encountered in high school.\r\n\r\nTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.","description_html":"\u003cp\u003eHere is a fun problem I encountered in high school.\u003c/p\u003e\u003cp\u003eTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.\u003c/p\u003e","function_template":"function y = graze(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 0.9566\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 2;\r\ny_correct = 3.8264;\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 6;\r\ny_correct = 34.4380;\r\nassert(isequal(graze(x),y_correct))\r\n\r\n%%\r\nx = 9;\r\ny_correct = 77.4855;\r\nassert(isequal(graze(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":4,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-07-23T11:07:08.000Z","updated_at":"2026-07-21T08:42:06.000Z","published_at":"2014-07-23T11:07:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHere is a fun problem I encountered in high school.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo cows are grazing in an enclosed square-shaped field of side length s meters. They are both tied by two ropes to the two adjacent corners of the field. Due to the ropes, they both will be able to graze only on a fraction of the field. Determine the the area of the field grazed by these two cows. Result should be rounded on 4 decimal points.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1003,"title":"Make a KITT-scanner on the command line","description":"Did you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with |fprintf(char(8));| (ASCII code 8 is a backspace), and the last character is removed. \r\nThis way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with   \r\n\r\n fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));\r\n\r\nYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. \r\nThe characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example \r\n\r\n kitt(10,'#=~-')\r\n\r\ntells it to show up as\r\n\r\n '#=~-------'\r\n\r\nIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\r\n\r\n '=#--------'\r\n\r\nfollowed by \r\n\r\n '~=#-------'\r\n\r\nand \r\n\r\n '-~=#------'\r\n\r\nand so on.\r\nYou see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S.\r\nThe 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen.\r\nTo check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). \r\nAnd off course, try to avoid just hard-coding the result. ","description_html":"\u003cp\u003eDid you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with \u003ctt\u003efprintf(char(8));\u003c/tt\u003e (ASCII code 8 is a backspace), and the last character is removed. \r\nThis way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with\u003c/p\u003e\u003cpre\u003e fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));\u003c/pre\u003e\u003cp\u003eYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. \r\nThe characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example\u003c/p\u003e\u003cpre\u003e kitt(10,'#=~-')\u003c/pre\u003e\u003cp\u003etells it to show up as\u003c/p\u003e\u003cpre\u003e '#=~-------'\u003c/pre\u003e\u003cp\u003eIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\u003c/p\u003e\u003cpre\u003e '=#--------'\u003c/pre\u003e\u003cp\u003efollowed by\u003c/p\u003e\u003cpre\u003e '~=#-------'\u003c/pre\u003e\u003cp\u003eand\u003c/p\u003e\u003cpre\u003e '-~=#------'\u003c/pre\u003e\u003cp\u003eand so on.\r\nYou see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S.\r\nThe 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen.\r\nTo check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). \r\nAnd off course, try to avoid just hard-coding the result.\u003c/p\u003e","function_template":"function scanner = kitt(l,s)\r\n  scanner = [s repmat(s(end),1,l-length(s))];\r\n  fprintf(scanner);\r\n  pause(2000/l);\r\n  fprintf(repmat([char(8) ' ' char(8)],1,l));\r\nend","test_suite":"%%\r\nl = 5;\r\ns = '#=~-';\r\ny_correct = strvcat({\r\n   '#=~--'\r\n   '=#---'\r\n   '~=#--'\r\n   '-~=#-'\r\n   '--~=#'\r\n   '---#='\r\n   '--#=~'\r\n   '-#=~-'\r\n   '#=~--'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 2;\r\ns = '*';\r\ny_correct = strvcat({\r\n   '**'\r\n   '**'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 5;\r\ns = '@ ';\r\ny_correct = strvcat({\r\n   '@    '\r\n   ' @   '\r\n   '  @  '\r\n   '   @ '\r\n   '    @'\r\n   '   @ '\r\n   '  @  '\r\n   ' @   '\r\n   '@    '\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n%%\r\nl = 6;\r\ns = '@\u003e\u003e*=~ ';\r\ny_correct = strvcat({\r\n   '@\u003e\u003e*=~'\r\n   '\u003e@*=~ '\r\n   '\u003e\u003e@~  '\r\n   '*\u003e\u003e@  '\r\n   '=*\u003e\u003e@ '\r\n   '~=*\u003e\u003e@'\r\n   ' ~=*@\u003e'\r\n   '  ~@\u003e\u003e'\r\n   '  @\u003e\u003e*'\r\n   ' @\u003e\u003e*='\r\n   '@\u003e\u003e*=~'\r\n});\r\nassert(isequal(kitt(l,s),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2012-10-30T08:09:52.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-10-19T05:48:39.000Z","updated_at":"2026-08-25T21:42:35.000Z","published_at":"2012-10-19T05:52:44.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDid you know that you can actually remove characters from the command-line window? Just send a 'backspace' character to the output, e.g. with\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efprintf(char(8));\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (ASCII code 8 is a backspace), and the last character is removed. This way, you can write a line, and remove it afterwards, by sending as many backspace characters as the line was long. However, you only move the cursor back, so when you want to clear a line, you have to move first the cursor to its beginning, then overwrite the line with blanks (spaces, ' '), and then move the cursor back once more. E.g. with\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ fprintf(repmat([char(8) ' ' char(8)],lenght_of_last_line,1));]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour task is to program a KITT-scanner (the red sweeping light in front of the black car in the TV-series Knight Rider) on the command line. The bar has a width specified by the first parameter L of the function. The characters which the bar is made of are specified in the 2nd parameter, S, of the function. The first character of S is the actual light. The last character is 'background', and the tail of the light is defined by the characters in between. For example\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ kitt(10,'#=~-')]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003etells it to show up as\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '#=~-------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt starts with the light on the left, tail to the right, and the light moving to the right in the next step. So,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '=#--------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efollowed by\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '~=#-------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ '-~=#------']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand so on. You see, the headlight supersedes the tail, when the head and tail overlap. Otherwise, the characters just show up with in the order defined in S. The 'frame rate' of the scanner should be 1/2 Hz, or one sweep back and forth in 2 seconds, but this can not be checked by Cody. But you are encouraged to watch the result on your own screen. To check your code, the function should output a character array with the full sequence, until the first step is repeated, with every row a step in the sequence (including the repeated last step). And off course, try to avoid just hard-coding the result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1696,"title":"Morse Code Generator! Try it!","description":"  .... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \r\n        .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \r\n  \r\n\r\n\r\n  \r\n\r\n  text = 'Morse code is FUN!'\r\n  Morse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--'\r\n\r\n\r\nJust a note: this uses international style Morse code found in:\r\n\r\nhttp://en.wikipedia.org/wiki/American_Morse_code\r\n","description_html":"\u003cpre class=\"language-matlab\"\u003e.... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \r\n      .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003etext = 'Morse code is FUN!'\r\nMorse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--'\r\n\u003c/pre\u003e\u003cp\u003eJust a note: this uses international style Morse code found in:\u003c/p\u003e\u003cp\u003e\u003ca href = \"http://en.wikipedia.org/wiki/American_Morse_code\"\u003ehttp://en.wikipedia.org/wiki/American_Morse_code\u003c/a\u003e\u003c/p\u003e","function_template":"function Morse_code_out = MorseCodeGenerator(text)\r\n  Morse_code_out = text_in;\r\nend","test_suite":"%%\r\nx = 'Morse code is FUN!';\r\ny_correct = '-- --- .-. ... .     -.-. --- -.. .     .. ...     ..-. ..- -. -.-.--';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = 'Am I 20, (who knows?)';\r\ny_correct = '.- --     ..     ..--- ----- --..--     -.--. .-- .... ---     -.- -. --- .-- ... ..--.. -.--.-';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = 'THE QUICK BROWN FOX JUMPS OVER THE LAZY DOG: or does he...';\r\ny_correct = '- .... .     --.- ..- .. -.-. -.-     -... .-. --- .-- -.     ..-. --- -..-     .--- ..- -- .--. ...     --- ...- . .-.     - .... .     .-.. .- --.. -.--     -.. --- --. ---...     --- .-.     -.. --- . ...     .... . .-.-.- .-.-.- .-.-.-';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n%%\r\nx = '1234567890';\r\ny_correct = '.---- ..--- ...-- ....- ..... -.... --... ---.. ----. -----';\r\nassert(isequal(MorseCodeGenerator(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":95,"test_suite_updated_at":"2019-09-16T11:37:52.000Z","rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-05T18:50:09.000Z","updated_at":"2026-07-15T14:09:32.000Z","published_at":"2013-07-09T15:55:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[.... . .-.. .-.. ---     . ...- . .-. -.-- --- -. . -.-.-- \\n      .-.. . - ...       -.. ---       ... --- -- .       -- --- .-. ... .       -.-. --- -.. . -.-.--             .-- . .-.. .-..       - .... .. ...       -- --- .-. ... .       -.-. --- -.. .       --. . -. . .-. .- - --- .-.       ..- ... . ...       - .... .       .. -. - . .-. -. .- - .. --- -. .- .-..       ... - -.-- .-.. .       -- --- .-. ... .       -.-. --- -.. . .-.-.-             - .... .       .-.-.-       .- -. -..              -- .- -.- .       ..- .--.       .- .-.. .-..       - .... .       -.-. --- -.. . --..--       - .... . .-. .       .. ...       --- -. .       ... .--. .- -.-. .       - .... .- -       ... . .--. .- .-. .- - . ...       .-.. . - - . .-. ...       .- -. -..       .....       ... .--. .- -.-. . ...       - .... .- -       ... . .--. .- .-. .- - .       .-- --- .-. -.. ... .-.-.-             ... --- -- .       .--. ..- -. -.-. - ..- .- - .. --- -.       .. ...       ..- ... . -.. .-.-.- .-.-.- .-.-.-             --- - .... . .-.       - .... . -.       - .... .- - --..--       .- .-.. .-..       -.-- --- ..-       -. . . -..       - ---       -.. ---       .. ...       - .- -.- .       .. -.       ... --- -- .       - -.-- .--. .       --- ..-.       - . -..- -       .. -.       - .... .       ..-. --- .-. --       --- ..-.       .-       ... - .-. .. -. --.       .- -. -..       - ..- .-. -.       .. -       .. -. - ---       .-       -- --- .-. ... .       -.-. --- -.. .       .-.. .. -. .        -.-. .... .- .-.       -.-. .-.. .- ... ...  --..--       .- ...       - .... .       . -..- .- -- .--. .-.. .       -... . .-.. --- .--       ... .... --- .-- ...  \\n\\ntext = 'Morse code is FUN!'\\nMorse_code_out = '-- --- .-. ... .       -.-. --- -.. .       .. ...       ..-. ..- -. -.-.--']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eJust a note: this uses international style Morse code found in:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/American_Morse_code\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://en.wikipedia.org/wiki/American_Morse_code\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1721,"title":"Backslang, odds are you used it at some point in time...","description":"So backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it.  Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end. \r\n\r\nHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\r\n\r\n  str = 'The sky is falling, the sky is falling, or is it?'\r\n\r\n  output = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?\r\n\r\nUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\r\n\r\nOodgay Ucklay!","description_html":"\u003cp\u003eSo backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it.  Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end.\u003c/p\u003e\u003cp\u003eHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003estr = 'The sky is falling, the sky is falling, or is it?'\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eoutput = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?\r\n\u003c/pre\u003e\u003cp\u003eUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\u003c/p\u003e\u003cp\u003eOodgay Ucklay!\u003c/p\u003e","function_template":"function output = backslang(str)\r\n  output = str;\r\nend","test_suite":"%%\r\nstr = 'The sky is falling, the sky is falling, or is it?'\r\noutput = 'Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'If Allen is Janes husband and Tom is Jill husband, who is Roys wife?'\r\noutput = 'Fiay Llenaay siay Anesjay usbandhay ndaay Omtay siay Illjay usbandhay, howay siay Oysray ifeway?'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'This is the sentence I will use.'\r\noutput = 'Histay siay hetay entencesay Iay illway seuay.'\r\nassert(isequal(backslang(str),output))\r\n%%\r\nstr = 'Christopher Columbus sailed the ocean blue!'\r\noutput = 'Hristophercay Olumbuscay ailedsay hetay ceanoay luebay!'\r\nassert(isequal(backslang(str),output))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":3,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":85,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":28,"created_at":"2013-07-17T16:39:49.000Z","updated_at":"2026-07-15T14:00:40.000Z","published_at":"2013-07-17T16:39:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo backslang is a language that can be used to communicate in an easy decode code, if people know the rules of decoding it. Well this backslang follows rules that are fairly customary. You take the first letter of a word and put it in the end, then add 'ay' on the end.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHatstay tiay! Onay oremay onay esslay. Ellway erehay reaay omesay xampleseay:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[str = 'The sky is falling, the sky is falling, or is it?'\\n\\noutput = Hetay kysay siay allingfay, hetay kysay siay allingfay, roay siay tiay?]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUstjay aay otenay, omesay unctuationpay ndaay apitalscay oday ountcay.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOodgay Ucklay!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":53064,"title":"Amazing circle of numbers 1 to n","description":"For given natural number n, create amazing circle of numbers 1 to n without a repeat.\r\nThis circle is that the sum of any two adjacent numbers is a perfect square.\r\nFor example, if n = 32,\r\n\r\nSo, output is\r\n                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\r\nIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\r\nIf there is no amazing circle vector, return empty vector [].","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 984px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 492px; transform-origin: 407px 492px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor given natural number n, create amazing circle of numbers 1 to n without a repeat.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis circle is that the sum of any two adjacent numbers is a perfect square.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if n = 32,\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 774px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 387px; text-align: left; transform-origin: 384px 387px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"768\" height=\"768\" style=\"vertical-align: baseline;width: 768px;height: 768px\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSo, output is\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eIf there is no amazing circle vector, return empty vector [].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = amazing_circle(n)\r\n  v = n;\r\nend","test_suite":"%%\r\nn=32;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=33;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=34;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=35;\r\nv = amazing_circle(n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=36;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=37;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))\r\n\r\n%%\r\nn=38;\r\nv = amazing_circle(n);\r\nv = v(1:n);\r\nflag = false;\r\nif length(unique(v)) == n \u0026 (min(v) == 1) \u0026 (max(v) == n)\r\n    for i = 1:n-1\r\n        lst(i) = mod(sqrt(v(i)+v(i+1)), 1) == 0;\r\n    end\r\n    lst(n) = mod(sqrt(v(n)+v(1)), 1) == 0;\r\n    if sum(lst) == n\r\n        flag = true;\r\n    end\r\nend\r\nassert(isequal(flag,true))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":517609,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2021-11-29T05:26:18.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2021-11-15T02:36:58.000Z","updated_at":"2026-09-17T23:13:59.000Z","published_at":"2021-11-15T04:44:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor given natural number n, create amazing circle of numbers 1 to n without a repeat.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis circle is that the sum of any two adjacent numbers is a perfect square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, if n = 32,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"768\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"768\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo, output is\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e                          [1 8 28 21 4 32 17 19 30 6 3 13 12 24 25 11 5 31 18 7 29 20 16 9 27 22 14 2 23 26 10 15]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the condition is satisfied, it is the correct answer regardless of the order of the vectors.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf there is no amazing circle vector, return empty vector 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":43574,"title":"Connect 4 (the boardgame)","description":"You are playing the popular game \"Connect 4\" ( \u003chttps://en.wikipedia.org/wiki/Connect_Four\u003e) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\r\n\r\nWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\r\n\r\nEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \"1\" (a chip of your opponent), \"2\" (one of your chips) or \"0\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\r\n\r\nGood luck!","description_html":"\u003cp\u003eYou are playing the popular game \"Connect 4\" ( \u003ca href = \"https://en.wikipedia.org/wiki/Connect_Four\"\u003ehttps://en.wikipedia.org/wiki/Connect_Four\u003c/a\u003e) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\u003c/p\u003e\u003cp\u003eWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\u003c/p\u003e\u003cp\u003eEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \"1\" (a chip of your opponent), \"2\" (one of your chips) or \"0\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\u003c/p\u003e\u003cp\u003eGood luck!\u003c/p\u003e","function_template":"function c = move(board)\r\n    % - the input board is a 5x7 matrix containing 0,1,2: The elements 0 are\r\n    % empty spaces, 1 are chips of your opponent and 2 are your chipt.\r\n    % - the output c is the column of your next chip, make sure this column\r\n    % has space left for your chip or the turn goes lost!\r\n\r\n    % select random available column\r\n    allC = find(sum(board~=0,1)\u003c5,7); % all not yet full columns\r\n    c = allC(randi(length(allC),1,1)); % random placement\r\nend","test_suite":"%%\r\ngames = 10;\r\nwinners = zeros(games,1);\r\nfor gamenum = 1:games % you play \"games\" different games\r\n    % init the board\r\n    board = zeros(5,7);\r\n    % function finding the index at which the chip will fall in column c\r\n    index = @(c,board) find(board(:,c)==0,1,'last');\r\n    % start the game\r\n    whoWon = 0;\r\n    done = false;\r\n    turn = 1;\r\n    while done == false\r\n        if turn == 1 % you oppenent's turn\r\n            % select random column\r\n            allC = find(sum(board~=0,1)\u003c5,7); % all not full columns\r\n            c = allC(randi(length(allC),1,1)); % random placement\r\n            % place chip in column c\r\n            board(index(c,board),c) = 1;\r\n        else % your turn\r\n            % which column\r\n            c = move(board);\r\n            % place chip in column c\r\n            i = index(c,board); % index\r\n            if ~isempty(i)\r\n                board(i,c) = 2;\r\n            else\r\n                disp('You have selected a full column, your turn goes lost')\r\n            end\r\n        end\r\n\r\n        % check for a 4-in-a-row\r\n        temp = board==turn;\r\n        % gather all possible 4-in-a-row lines\r\n            lines = cell(22,1);\r\n            % horizontal\r\n            for i = 1:5\r\n                lines{i} = temp(i,:)';\r\n            end\r\n            % vertical\r\n            for i = 1:7\r\n                lines{i+5} = temp(:,i);\r\n            end\r\n            % diagonal \\\r\n            lines{13} = diag(temp(2:end,:));\r\n            for i = 1:4\r\n                lines{i+13} = diag(temp(:,i:end));\r\n            end\r\n            % diagonal /\r\n            temp = fliplr(temp);\r\n            lines{18} = diag(temp(2:end,:));\r\n            for i = 1:4\r\n                lines{i+18} = diag(temp(:,i:end));\r\n            end\r\n        for i = 1:length(lines)\r\n            % find the maximum number of the same chips in this row\r\n            temp = diff([0; lines{i}; 0]);\r\n            if max(find(temp==-1,7)-find(temp==1,7))==4\r\n                % game is won!\r\n                whoWon = turn;\r\n                done = true;\r\n            end\r\n        end\r\n        % is the board full without a winner?\r\n        if sum(board==0)==0\r\n            done = true;\r\n        end\r\n        % switch turns\r\n        turn = 3-turn;\r\n    end % end of one game\r\n    winners(gamenum) = whoWon;\r\nend\r\ndisp(['Game results (#won/#lost/#draw): ' num2str(sum(winners==2)) '/' num2str(sum(winners==1)) '/' num2str(sum(winners==0))])\r\n% Did you win all 10 games?\r\nassert(isequal(sum(winners==2),games))","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-18T09:14:38.000Z","updated_at":"2026-05-25T01:57:26.000Z","published_at":"2016-10-18T09:14:38.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are playing the popular game \\\"Connect 4\\\" (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Connect_Four\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://en.wikipedia.org/wiki/Connect_Four\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;) against Matlab. Luckily, Matlab isn't trying to hard and just places its chips randomly.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function which plays the game for you. As starting point you are given the same function which you opponent is using (random placement). But you'll have to do better, because you will have to crush Matlab by winning 10 games in a row in order to pass this test!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEach time your function as called it is your turn to make a move. The input of the function is a 5x7 matrix, representing the game board, containing either \\\"1\\\" (a chip of your opponent), \\\"2\\\" (one of your chips) or \\\"0\\\" (an empty space). Calculate your best move and output the column index of your next chip (make sure this column isn't full yet or your turn is lost).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGood luck!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"}],"errors":[],"facets":[[{"value":"Strings II","count":3,"selected":false},{"value":"The Movies","count":3,"selected":false},{"value":"Basics on π","count":2,"selected":false},{"value":"Board Games II","count":2,"selected":false},{"value":"Board Games I","count":1,"selected":false},{"value":"Card Games","count":1,"selected":false},{"value":"Cody Challenge","count":1,"selected":false},{"value":"Matrix Patterns III","count":1,"selected":false},{"value":"Strings III","count":1,"selected":false}],[{"value":"easy","count":31,"selected":false},{"value":"medium","count":19,"selected":false},{"value":"hard","count":7,"selected":false}]],"term":"tag:\"fun\"","page":1,"per_page":50,"sort":"map(difficulty_value,0,0,999) asc"}}