Abstract:Through studying on one of the reasons leading to the high cost of mutation testing which is the large number of mutants produced during the process of testing, a mutants reduction method of clustering based on genetic algorithm was proposed. Mutants with similar characteristics would be placed in the same cluster, and then randomly selected one from each cluster as a representative in order to reduce the mutants. The experimental results show that: 1) the proposed method can reduce mutants without compromising the adequacy of the constituted test suite; 2) and compared with K-means algorithm and agglomerative clustering algorithm, it can automatically form an appropriate number of clusters, and is more effective.