一种模糊K-means算法在测试用例集约简中的应用

Fuzzy K-Means Algorithm of Software Testing Using Case Reduction

为了提高软件测试用例集约简的成效,提出一种基于模糊K-means的软件测试集用例约简算法,引入模糊划分思想,结合测试需求集,从各个簇中抽取测试用例,尽可能地发现相似的用例.实验结果表明:算法能够最小化约简用例集,用例集覆盖范围最广泛,错误率检测较高.

To improve the effectiveness of the software test set reduction,a software test set case reduction algorithm based on fuzzy K means is proposed.The fuzzy partition idea is introduced.The test suite is extracted from each cluster,finded similar cases.Experimental results showed that the algorithm can minimize the reduction case set,covers the most extensive and highly detect the error rate.