Equivalent Mutants in the Wild: Identifying and Efficiently Suppressing Equivalent Mutants for Java']Java Programs

The presence of equivalent 'mutants has long been considered a major obstacle to the widespread adoption of mutation analysis and mutation testing. This paper presents a study on the types and prevalence of equivalent mutants in real-world Java programs. We conducted a ground-truth analysis of 1,992 mutants, sampled from 7 open source Java projects. Our analysis identified 215 equivalent mutants, which we grouped based on two criteria that describe why the mutants arc equivalent and how challenging their detection is. From this analysis, we observed that (1) the median equivalent mutant rate across the 7 projects is 2.97'7,, (2) many equivalent mutants are caused by common programming patterns and their detection is not much more complex than structural pattern matching over an abstract syntax tree. Based on the findings of our ground-truth analysis, we developed Equivalent Mutant Suppression (EMS), a technique that comprises 10 efficient and targeted analyses. We evaluated EMS on 19 opensource Java projects, comparing the effectiveness and efficiency of EMS to two variants of Trivial Compiler Equivalence (ICE), the current state of the art in equivalent mutant detection. Additionally, we analyzed all 9,047 equivalent mutants reported by any tool to better understand the types and frequencies of equivalent mutants found. Overall, EMS detects 8,776 equivalent mutants within 325 seconds; ICE detects 2,124 equivalent mutants in 2,938 hours.