Accelerating Regression Testing for Scaled Self-Driving Cars with Lightweight Virtualization -- A Case Study

Engineering software for smart cyber-physical systems (sCPS) challenges developers as they have to deal with uncertain and volatile stimuli data perceived by sensors. Regression testing of a sCPS is time-consuming on sequential execution. However, sequential testing can be parallelized depending on the system calls used in the system-under-test. In a case study about accelerating regression testing for scaled self-driving cars, we evaluate the use of namespace-separation based lightweight virtualization that powers solutions like Docker or Google´s lmctfy. After transparently adding lightweight virtualization to Cxx Test that is used for regression testing, the total test execution time could be reduced from previously over 12min by more than 62% to less than 5min. Thus, the technology for today´s lightweight virtualization can also be used to safely accelerate test-runners without changing existing test cases.