Is mutation an appropriate tool for testing experiments?

The empirical assessment of test techniques plays an important role in software testing research. One common practice is to instrument faults, either manually or by using mutation operators. The latter allows the systematic, repeatable seeding of large numbers of faults; however, we do not know whether empirical results obtained this way lead to valid, representative conclusions. This paper investigates this important question based on a number of programs with comprehensive pools of test cases and known faults. It is concluded that, based on the data available thus far, the use of mutation operators is yielding trustworthy results (generated mutants are similar to real faults). Mutants appear however to be different from hand-seeded faults that seem to be harder to detect than real faults.