Towards differential fuzzing to reduce manual efforts to identify equivalent mutants: A preliminary study

Mutation testing is a technique that assesses the effectiveness of a set of test cases by introducing changes to the source code and checking whether the test cases can detect them. However, mutation testing is costly, and many academic efforts have been directed to improve its effectiveness and reduce costs. One of the challenges related to mutation testing remains in the equivalent mutant problem. Fuzzing, as a search technique, can find test cases that the developers might not have addressed in unit testing, and it could be used to identify equivalent mutants. In this paper, we present a preliminary study that investigates the use of differential fuzzing to identify equivalent mutants. To identify equivalent mutants, one approach is to set a timeout period after which any surviving mutants are considered equivalent. In our experiment, a 3-minute timeout yielded an accuracy rate of 97%. In conclusion, differential fuzzing can be used to identify equivalent mutants accurately at a reasonable time, especially for projects that maintain a robust seed corpus for fuzzing.