Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (22): 66-73.DOI: 10.3778/j.issn.1002-8331.2001-0152

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Function-Level Software Fault Location Based on Genetic Algorithm

HUANG Qingyan, MU Yongmin, CUI Zhanqi, ZHANG Zhihua   

  1. 1.Computer College, Beijing Information Science and Technology University, Beijing 100101, China
    2.Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China
  • Online:2020-11-15 Published:2020-11-13



  1. 1.北京信息科技大学 计算机学院,北京 100101
    2.北京信息科技大学 网络文化与数字传播北京市重点实验室,北京 100101


For fault location in software development based on function call path and genetic algorithm, this paper proposes a software fault location method called FGAFL. Firstly, the proposed method transforms fault location into combinatorial optimization in software testing, and constructs fitness function based on the influence of function call path. Then, to obtain the optimal solution, the method searches the candidate fault distribution with high suspicious degree in the candidate population iteratively by genetic algorithm. Finally, according to the optimal solution, the functions in the program are sorted according to the suspicious degree, while the proposed method checks the functions in that order and locate the faults. Experimental results show that FGAFL can reduce the amount of computation and the scope of code review effectively, so as to improve the accuracy and efficiency of fault location.

Key words: fault location, function call path, genetic algorithm, fitness function



关键词: 错误定位, 函数调用路径, 遗传算法, 适应度函数