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Mutagen4J : Effective Mutant Generation Tool for Java Programs
Yiru Jeon, Yunho Kim, Shin Hong, Moonzoo Kim
Mutation analysis (or software mutation analysis) generates variants of a target program by injecting systematic code changes to the target program, and utilizes the variants to analyze the target program behaviors. Effective mutation analyses require adequate mutation operators that generate diverse variants for use in the analysis. However, the current mutation analysis tools for Java programs have limitations, since they support only limited types of mutation operators and do not support recent language features such as Java8. In this study, we present Mutagen4J, a new mutant generation tool for Java programs. Mutagen4J additionally supports mutation operators recently shown to generate various mutants and fully supports recent Java language features. The experimental results show that Mutagen4J generates useful mutants for analyses 2.3 times more than the existing Java mutation tools used for the study.
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