基于程序变异和高斯混合聚类的错误定位技术  

Fault Localization Technology Based on Program Mutation and Gaussian Mixture Model

作　　者：张慧 ZHANG Hui(School of Computer Science,Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 212003,China)

机构地区：[1]江苏科技大学计算机学院,江苏镇江212003

出　　处：《计算机科学》2021年第S01期572-574,595,共4页Computer Science

摘　　要：错误定位的效率依赖回归测试用例的质量,然而相同相似的测试用例影响着错误定位的效率。针对以上问题,文中提出了利用基于改进的人工免疫技术的程序变异产生多个变异体,然后通过高斯混合聚类约简变异体进行错误定位。实验结果表明,相比其他方法,所提方法可以提高错误定位的效率。The efficiency of fault localization relies on the quality of regression test cases,while the same and similar test cases affect the efficiency of fault localization.In order to solve the above problem,this paper proposes program mutation based on the improved artificial immune technology to generate multiple mutants,and then reduces the mutants for fault localization by Gaussian mixture model.The experimental results show that the proposed method can improve the efficiency of fault localization compared with other methods.

关 键 词：错误定位 程序变异 人工免疫 高斯混合聚类 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]