Automatic Test Case Generation and Optimization Based on Mutation Testing

Abstract

Based on defect implantation mutation testing technique not only serves as a standard for evaluating test cases but also guides how to generate high-quality test case sets. In order to reduce the number of mutants, we propose a mutation operator selection strategy according to Selective Mutation. From 19 mutation operators of Mujava we select 5 mutation operators to obtain a subset. Test cases using this subset are able to achieve an average variation score of more than 95% on the variants of the complete set. Then we propose a test case generation method combining mutation testing with a genetic algorithm. The crossover, insertion, change, and deletion operators of the test case set are redefined, and the test cases are optimized. Finally compared with some algorithms and tools we obtain a set of test cases with higher coverage and higher mutation score.