基于程序变异和高斯混合聚类的错误定位技术

doi:10.11896/jsjkx.200500121

摘要/Abstract

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。

关键词: 程序变异, 错误定位, 高斯混合聚类, 人工免疫

Abstract: 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.

Key words: Artificial immune, Fault localization, Gaussian mixture model, Program mutation

中图分类号:

TP311.5

张慧. 基于程序变异和高斯混合聚类的错误定位技术[J]. 计算机科学, 2021, 48(6A): 572-574. https://doi.org/10.11896/jsjkx.200500121

ZHANG Hui. Fault Localization Technology Based on Program Mutation and Gaussian Mixture Model[J]. Computer Science, 2021, 48(6A): 572-574. https://doi.org/10.11896/jsjkx.200500121

参考文献

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