Keeping Mutation Test Suites Consistent and Relevant with Long-Standing Mutants
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Abstract (arXiv)
Mutation testing has been demonstrated to be one of the most powerful fault-revealing tools in the tester's tool kit. Much previous work implicitly assumed it to be sufficient to re-compute mutant suites per release. Sadly, this makes mutation results inconsistent; mutant scores from each release cannot be directly compared, making it harder to measure test improvement. Furthermore, regular code change means that a mutant suite's relevance will naturally degrade over time. We measure this degradation in relevance for 143,500 mutants in 4 non-trivial systems finding that, on overage, 52% degrade. We introduce a mutant brittleness measure and use it to audit software systems and their mutation suites. We also demonstrate how consistent-by-construction long-standing mutant suites can be identified with a 10x improvement in mutant relevance over an arbitrary test suite. Our results indicate that the research community should avoid the re-computation of mutant suites and focus, instead, on long-standing mutants, thereby improving the consistency and relevance of mutation testing.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 22 Dec 2022.
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- 2025Mutation-Guided LLM-based Test Generation at Metacited by 23
- 2025Mutation-Guided LLM-based Test Generation at Meta22 Jan 2025