基于影响分析的回归测试优先级错误定位方法  

Regression Testing Prioritization Fault Localization Method Based on Influence Analysis

作　　者：张慧[1] ZHANG Hui(School of Computer Science and Engineering, Southeast University, Nanjing 211189, China)

机构地区：[1]东南大学计算机科学与工程学院,南京211189

出　　处：《计算机科学》2016年第10期182-189,共8页Computer Science

摘　　要：基于程序行为特征的错误定位方法由于只孤立地看待每个程序实体,使其错误定位的效率受到影响,而回归测试错误定位又由于需要执行全部测试用例将大大增加开发和测试成本。针对以上问题,提出一种基于影响分析的回归测试优先级错误定位方法,该方法将联合依赖图、基于程序行为特征的错误定位方法和回归测试优先级进行有机结合。实验结果表明,与Ochiai,Tarantula,PPDG,CP和Naish等经典方法相比,该方法可更加有效地定位软件错误。Since the fault localization method based on programs behavior characteristics sees every program entity iso- lated, the efficiency of fault localization is influenced. And since the regression test fault localization needs to execute all test cases, the developing and testing costs increase largely. In view of the above problems, this paper put up a regres- sion testing prioritization fault localization method based on influence analysis, which organically integrates the joint de- pendency graph,the fault localization method based on programs behavior characteristics and the regression testing prioritization. The experimental results show that compared with classical methods such as Ochiai, Tarantula, PPDG, CP and Naish, this method can more efficiently position software errors.

关 键 词：错误定位 测试用例 回归测试优先级 联合依赖图 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]