Mutant Hierarchies Support Selective Mutation
Mutation testing attempts to assess the quality of a test set by its ability to distinguish the program under test from its mutants. One of the main difficulties faced in practice is due to the large number of mutants that can be generated for a program under test. Earlier research to solve this problem has suggested variants of mutation testing, and finding an effective set of mutation operators referred to as selective mutation. This paper presents an alternative approach for reducing the
... or reducing the cost of testing by identifying hierarchies among first-order mutants. The key idea is to evaluate the strength of a mutant with respect to other mutants and ignore "weaker" mutants during testing. Unlike previous approaches, our method is formal and it is guaranteed that the effectiveness of a test suite will be identical with that can be achieved using all mutants. The theory described here is also applicable to the quantitative assessment of testing effort and can be used to guide successive testing steps in fault-based testing. We present an empirical evaluation to find reduction in the test effort using mutant classification and show that it supports selective mutation. Povzetek: Metodo testiranja z mutanti so izboljšali s hierarhijo mutacij, ki izloča slabše mutante.