Check safety-related diagnostic settings for parameters

mathworks.hism.hisl_0302

Dependencies: Simulink^® Check™

Usage: High-Integrity System Modeling

Guideline: hisl_0302: Configuration Parameters > Diagnostics > Data Validity > Parameters

Description

This check verifies that the model configuration uses optimal parameter settings that apply to parameters when generating code for a safety-related application.

Recommended Actions and Results

Review the violations that are flagged by the check and the recommended action for fixing the issue. After applying the changes, save the model and rerun the check analysis.

You can use the Fix button to allow the Model Advisor to fix flagged violations. For this check, the Model Advisor configures model diagnostic settings that apply to parameters and that can impact safety.

Modeling Condition	Recommended Action
The diagnostic that detects when a parameter downcast occurs is set to none or warning. A downcast to a lower signal range can result in numeric overflows of parameters, resulting in unexpected behavior.	Set model configuration parameter Detect downcast to error.
The diagnostic that detects when a parameter underflow occurs is set to none or warning. When the data type of a parameter does not have enough resolution, the parameter value is zero instead of the specified value. This can lead to incorrect operation of generated code.	Set model configuration parameter Detect underflow to error.
The diagnostic that detects when a parameter overflow occurs is set to none or warning. Numeric overflows can result in unexpected behavior. To avoid this unexpected behavior, find and fix numeric overflows in safety-related applications.	Set model configuration parameter Detect overflow to error.
The diagnostic that detects when a parameter loses precision is set to none or warning. Not detecting such errors can result in a parameter being set to an incorrect value in the generated code.	Set model configuration parameter Detect precision loss to error.
The diagnostic that detects when an expression with tunable variables is reduced to its numerical equivalent is set to none or warning. This can result in a tunable parameter unexpectedly not being tunable in generated code.	Set model configuration parameter Detect loss of tunability to error.

Capabilities and Limitations

• Does not run on library models

• Does not allow exclusions of blocks or charts

• Does not require model compilation

Version History

Introduced in R2007b