SimRT: an automated framework to support regression testing for data races

Tingting Yu, Witawas Srisa-an, Gregg Rothermel
2014 Proceedings of the 36th International Conference on Software Engineering - ICSE 2014  
Concurrent programs are prone to various classes of difficult-todetect faults, of which data races are particularly prevalent. Prior work has attempted to increase the cost-effectiveness of approaches for testing for data races by employing race detection techniques, but to date, no work has considered cost-effective approaches for re-testing for races as programs evolve. In this paper we present SIMRT, an automated regression testing framework for use in detecting races introduced by code
more » ... ications. SIMRT employs a regression test selection technique, focused on sets of program elements related to race detection, to reduce the number of test cases that must be run on a changed program to detect races that occur due to code modifications, and it employs a test case prioritization technique to improve the rate at which such races are detected. Our empirical study of SIMRT reveals that it is more efficient and effective for revealing races than other approaches, and that its constituent test selection and prioritization components each contribute to its performance.
doi:10.1145/2568225.2568294 dblp:conf/icse/YuSR14 fatcat:bowit4mnezfqhhyykzeczxsi6q