A Method and Tool for Test Optimization for Automotive Controllers

Completely automatic generation of tests from formal executable test models of industrial size still looks like a “holy grail”, in spite of significant progress in model-based testing research and tool development. Realizing this, we follow a more down-to-earth approach by assuming that, even if a test model is available, the test expert manually derives powerful test fragments and what remains to be automated is chaining them into an optimal test. Focusing on this task, we develop a test optimization framework using an FSM extended with input variables and clocks, which reflects important features of Simulink/Stateflow statecharts. The test optimization is expressed as the Asymmetric Travelling Salesman Problem (ATSP). We show how this approach can be used for solving some testing problems specific to automotive controllers. We describe a proof-of-concept prototype, implementing the proposed approach, which we tested on a case study of a particular controller available along with some tests. Experiments with the prototype indicate that the approach scales well for hundreds of tests.