一种基于频谱信息并结合碰集和遗传算法的缺陷定位方法

在软件研制过程中,缺陷定位是一个重要的研究课题。但是,实际软件中的缺陷数量无法被预先判定,且已有的单缺陷定位方法不易使用,已有的多缺陷定位方法存在定位效率不高的问题。基于此,文中对多缺陷定位方法GAMFL进行了研究和改进,提出了基于频谱信息并结合碰集和遗传算法的缺陷定位方法GAHIT。该方法定义了定位基本块,并用其替代语句进行缺陷定位,缩小了搜索范围；在初始种群的构造过程中,提出了采用求解失败用例执行路径碰集的方法,优化了初始种群的生成,并给出了新的适应度函数的计算方法,提高了算法的整体执行效率；最后针对遗传算法的结果,给出了缺陷检查策略,提高了在最优种群中查找缺陷的准确性。实验结果表明,所提方法能够有效处理缺陷数量未知情况下的定位问题,在单缺陷和多缺陷程序中都有较好的定位效果。

New Spectrum-based Fault Localization Method Combining Hitting Set and Genetic Algorithm

Fault localization is an important research topic in the process of software development.However,the number of faults in the actual software cannot be determined in advance.The available single fault localization technique is not convenient to be used,and the available multi-fault localization technique is of low locating efficiency.This paper studied and improved the multi-fault localization technique GAMFL,and proposed a new spectrum-based fault localization methoid combining hitting set and genetic algorithm(GAHIT).In this method,the basic block for localization is defined and used to replace statements to localize faults,narrowing the search range.In the process of constructing initial population,the method of solving the hitting sets of execution path of failure test cases is presented to optimize the generation of initial population,and a new method for calculating fitness function is also presented to improve the total efficiency of the algorithm.According to the results of genetic algorithm,the fault detecton strategy is presented to improve the accuracy of localizing faults in the optimal group.The experiment results show that the proposed method is effective in solving the problem of localizing programs with unknown number of faults,and has good performance when localizing faults in both single fault programs and multi-fault programs.