Simulink Design Verifier
Identify design errors, prove requirements compliance, and generate tests
Simulink Design Verifier™ uses formal methods to identify hidden design errors in models. It detects blocks in the model that result in integer overflow, dead logic, array access violations, and division by zero. It can formally verify that the design meets functional requirements. For each design error or requirements violation, it generates a simulation test case for debugging.
Simulink Design Verifier generates test cases for model coverage and custom objectives to extend existing requirements-based test cases. These test cases drive your model to satisfy condition, decision, modified condition/decision (MCDC), and custom coverage objectives. In addition to coverage objectives, you can specify custom test objectives to automatically generate requirements-based test cases.
Support for industry standards is available through IEC Certification Kit (for IEC 61508 and ISO 26262) and DO Qualification Kit (for DO-178).
Get Started:
Run-Time and Diagnostic Errors
Before you run simulations, you can detect run-time and modeling errors, including integer overflow, division by zero, array out of bounds, subnormal values, and floating-point errors as well as data validity errors.
Dead Logic
Find objects in your model that cannot be activated during simulation and execution of generated code. |
Viewing dead logic in your models.
Test Cases to Increase Coverage
Augment and extend existing manually created test cases to address incomplete model coverage. |
Requirements-Based Test Cases
Generate test cases from models of system requirements.
Test Cases for C/C++ Code
Generate test cases to increase coverage of generated code and C/C++ code called from Simulink® blocks and in Stateflow® charts.
Generating tests for models that call C code.
Safety Requirements
Verify that your design behaves according to formally defined safety requirements that you express using MATLAB®, Simulink, and Stateflow.
Express requirements using Simulink.
Simplify Models for Deployment
After you have fully validated your master variants model, use Variant Reducer to generate a reduced model for a subset of valid configurations. All related files and variable dependencies are also reduced. The reduced artifacts are packaged in a separate folder to enable easy deployment and sharing with customers and partners.
Creating a reduced model.
Justify Design Errors
Create filter and justification rules for design error checks after analysis for iterative workflows
Detect Data Store Memory Access Violations
Analyze models for Data Store Memory errors such as read-before-write, write-after-read, and write-after-write
Custom Code Support
Detect design errors in C/C++ custom code in models and Stateflow charts
Reduce Analysis Time for Team-based Workflows
Share and reuse model representation across teams for iterative workflows
Test Extension for Parameter Workflows
Modify parameter constraints across analysis runs when extending manually written test cases
Complex Type Support
Analyze and generate test cases for models with Complex data types
See the release notes for details on any of these features and corresponding functions.
