||Build coverage-compatible MEX-function from C/C++ code|
Develop effective tests with model coverage.
Before starting a model coverage analysis, you specify several model coverage recording options.
Create and run test cases using model coverage MATLAB® commands
View coverage results of a model by coloring its elements.
Use model coverage for MATLAB Function blocks and interpret the results.
Use the Model Coverage tool to determine the extent to which a model test case exercises simulation control flow paths through a model.
Analyze model coverage for C/C++ S-Functions.
Collect model coverage when a model has multiple Model blocks that reference the same model.
This example illustrates how Simulink Verification and Validation records the MCDC metric for a cascade of Logical Operator blocks.
Create and view cumulative coverage results for a model with a reusable subsystem.
Configure code coverage for SIL and PIL simulations and review results.
Validate your model tests by measuring how thoroughly the model objects are tested.
Simulink® Verification and Validation™ can perform several types of coverage analysis.
If you have Embedded Coder®, Simulink Verification and Validation can perform several types of code coverage analysis for models in software-in-the-loop (SIL) mode, processor-in-the-loop (PIL) mode, and for the code within supported S-Function blocks.
This model includes various patterns of cascaded Logical Operator blocks.
Learn how inlined parameters, block reduction, and conditional input branch execution can affect your model coverage data.
Collect cumulative model coverage from successive simulation runs.
Model objects that receive model coverage during simulation.
Simulink objects that do not receive coverage.