Statement-Oriented Mutant Reduction Strategy for Mutation Based Fault Localization

Mutation Based Fault Localization(MBFL) is a fault localization technique based on mutation analysis, which precisely identifies the location of fault but incurs a high execution cost, since it needs to execute the test suite on a large amount of mutants. Reduction strategies proposed are usually regarding selecting mutation operators or sampling mutants directly, meanwhile at the cost of losing precision of fault localization. This paper proposes a Statement-Oriented Mutant Reduction strategy (SOME), which selects a proportion of mutants at the statement level, specifically, the statements covered by failed tests. SOME keeps the advantage of using whole types of mutation operators, and further considers the increase of mutants' diversity to avoid the precision loss of fault localization. Empirical studies are conducted on 112 faulty versions from 7 benchmark programs, and the results indicate that SOME can reduce 73.51%–79.98% mutation execution cost while keeping almost the same fault location precision as the original MBFL without reduction.