Dependency-Based Test Case Selection and Prioritization in Embedded Systems

Embedded systems in automotive engineering are getting more and more complex due to a higher rate of integration and shared usage of sensor signals. A common solution to testing these systems is deriving test cases from models, so called model-based testing. In practice, generated test suites are typically very huge and have to be reduced by methods of regression-test selection and prioritization. In our field of application, we additionally suffer from the lack of knowledge on system internals like the source code. Therefore, our approach is based on dependences between the components of embedded systems. The model we use is derived from the system architecture and system requirements. We are using graph algorithms for selecting and prioritizing test cases to run on a certain system version. First statistical evaluations and the current implementation already have shown promising reduction of test-cases for regression testing.