Volkswagen kindly invited me to give a talk in their seminar series “Code Analysis and Beyond” on our research in test suite evaluation and optimisation. I report on glass-box methods to detect pseudo-tested code as well as code that is too trivial to test. Furthermore, I describe black-box techniques that use traces and data flow on the system integration level.

Here are the slides:

Here are the papers that report on these research contributions:

R. Niedermayr, T. R ̈ohm, and S. Wagner. Too trivial to test? an inverse view on defect prediction to identify methods with low fault risk. PeerJ Computer Science, 5:e187, 2019.

R. Niedermayr, E. Juergens, and S. Wagner. Will my tests tell me if i break this code? In 2016 IEEE/ACM International Workshop on Continuous Software Evolution and Delivery (CSED), pages 23–29. IEEE, 2016.

S. Vöst and S. Wagner. Trace-based test selection to support continuous integration in the automotive industry. In Proceedings of the International Workshop on Continuous Software Evolution and Delivery, pages 34–40, 2016.

D. Hellhake, T. Schmid, and S. Wagner. Using data flow-based coverage criteria for black-box integration testing of distributed software systems. In 2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST), pages 420–429. IEEE, 2019.