This edition of the tool competition on regression testing of self-driving cars (SDCs) at the International Workshop on Search-Based and Fuzz Testing aims to provide a platform for software testers to submit their tools addressing the test prioritization problem for simulation-based testing of SDCs, which is considered an emerging and vital domain. The competition provides an advanced software platform and representative case studies to ease participants' entry into SDC regression testing, enabling them to develop their initial test generation, selection, and prioritization tools for SDCS. In this second edition, the competition includes one tool. The tool was evaluated using (regression) metrics for test prioritization, as well as compared with a baseline random approach. This paper provides an overview of the competition, detailing its context, framework, participating tools, evaluation methodology, and key findings.
SBFT Tool Competition 2026-CPS-SDC Regression Testing Track / Aryan, P., Fulcini, T., Starace, L.L.L., Birchler, C., Panichella, S.. - (2026), pp. 19-22. (19th International Workshop on Search-Based and Fuzz Testing, SBFT 2026 bra 2026) [10.1145/3786155.3795699].
SBFT Tool Competition 2026-CPS-SDC Regression Testing Track
Starace L. L. L.;
2026
Abstract
This edition of the tool competition on regression testing of self-driving cars (SDCs) at the International Workshop on Search-Based and Fuzz Testing aims to provide a platform for software testers to submit their tools addressing the test prioritization problem for simulation-based testing of SDCs, which is considered an emerging and vital domain. The competition provides an advanced software platform and representative case studies to ease participants' entry into SDC regression testing, enabling them to develop their initial test generation, selection, and prioritization tools for SDCS. In this second edition, the competition includes one tool. The tool was evaluated using (regression) metrics for test prioritization, as well as compared with a baseline random approach. This paper provides an overview of the competition, detailing its context, framework, participating tools, evaluation methodology, and key findings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


