Automatically detecting equivalent mutants and infeasible paths

Mutation testing is a technique for testing software units that has great potential for improving the quality of testing, and thereby increasing our ability to assure the high reliability of critical software. It will be shown that recent advances in mutation research have brought a practical mutation testing system closer to reality. One recent advance is a partial solution to the problem of automatically detecting equivalent mutant programs. Equivalent mutants are currently detected by hand, which makes it very expensive and time-consuming. The problem of detecting equivalent mutants is a speci c instance of a more general problem, commonly called the feasible path problem, which says that for certain structural testing criteria some of the test requirements are infeasible in the sense that the semantics of the program imply that no test case satis es the test requirements. Equivalent mutants, unreachable statements in path testing techniques, and infeasible DU-pairs in data ow testing are all instances of the feasible path problem. This paper presents a technique that uses mathematical constraints, originally developed for test data generation, to automatically detect some equivalent mutants and infeasible paths. Keywords|software testing, mutation testing, constraints, feasible path analysis The Journal of Software Testing, Veri cation, and Reliability, Vol 7, No. 3, pages 165{192, September 1997.