An Empirical Study on the Scalability of Selective Mutation Testing

Abstract

Software testing plays an important role in ensuring software quality by running a program with test suites. Mutation testing is designed to evaluate whether a test suite is adequate in detecting faults. Due to the expensive cost of mutation testing, selective mutation testing was proposed to select a subset of mutants whose effectiveness is similar to the whole set of generated mutants. Although selective mutation testing has been widely investigated in recent years, many people still doubt whether it can suit well for large programs. To study the scalability of selective mutation testing, we systematically explore how the program size impacts selective mutation testing through four projects (including 12 versions all together). Based on the empirical study, for programs smaller than 16 KLOC, selective mutation testing has surprisingly good scalability. In particular, for a program whose number of lines of executable code is E, the number of mutants used in selective mutation testing is proportional to Ec, where c is a constant whose value is between 0.05 and 0.25.