Hybrid Regression Test Selection

Regression testing is crucial but can be extremely costly. Regression Test Selection (RTS) aims to reduce regression testing cost by only selecting and running the tests that may be a!ected by code changes. To date, various RTS techniques analyzing at di!erent granularities (e.g., at the basic-block, method, and "le levels) have been proposed. RTS techniques working on "ner granularities may be more precise in selecting tests, while techniques working on coarser granularities may have lower overhead. According to a recent study, RTS at the "le level (FRTS) can have less overall testing time compared with a "ner grained technique at the method level, and represents state-of-the-art RTS. In this paper, we present the "rst hybrid RTS approach, HyRTS, that analyzes at multiple granularities to combine the strengths of traditional RTS techniques at di!erent granularities. We implemented the basic HyRTS technique by combining the method and "le granularity RTS. The experimental results on 2707 revisions of 32 projects, totalling over 124 Million LoC, demonstrate that HyRTS outperforms state-of-the-art FRTS signi"cantly in terms of selected test ratio and the o!ine testing time. We also studied the impacts of each type of method-level changes, and further designed two new HyRTS variants based on the study results. Our additional experiments show that transforming instance method additions/deletions into "le-level changes produces an even more e!ective HyRTS variant that can signi"cantly outperform FRTS in both o!ine and online testing time. ACM Reference Format: Lingming Zhang. 2018. Hybrid Regression Test Selection. In ICSE ’18: ICSE ’18: 40th International Conference on Software Engineering , May 27-June 3, 2018, Gothenburg, Sweden. ACM, New York, NY, USA, 11 pages. https: //doi.org/10.1145/3180155.3180198