2004 | OriginalPaper | Buchkapitel
How to Overcome the Equivalent Mutant Problem and Achieve Tailored Selective Mutation Using Co-evolution
verfasst von : Konstantinos Adamopoulos, Mark Harman, Robert M. Hierons
Erschienen in: Genetic and Evolutionary Computation – GECCO 2004
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The use of Genetic Algorithms in evolution of mutants and test cases offers new possibilities in addressing some of the main problems of mutation testing. Most specifically the problem of equivalent mutant detection, and the problem of the large number of mutants produced. In this paper we describe the above problems in detail and introduce a new methodology based on co-evolutionary search techniques using Genetic Algorithms in order to address them effectively. Co-evolution allows the parallel evolution of mutants and test cases. We discuss the advantages of this approach over other existing mutation testing techniques, showing details of some initial experimental results carried out.