利用改进遗传算法的软件故障定位辅助测试用例生成方法  

Using improved genetic algorithm for software fault localization aided test case generation

作　　者：杨波 何宇泽[3] 许福 陈志泊[1,2] YANG Bo;HE Yuze;XU Fu;CHEN Zhibo(School of Information,Beijing Forestry University,Beijing 100083,China;Engineering Research Center for Forestry Goriented Intelligent Information Processing,National Forestry and Grassland Administration,Beijing 100083,China;School of Information,North China of Science and Technology,Beijing 100144,China)

机构地区：[1]北京林业大学信息学院,北京100083 [2]国家林业和草原局林业智能信息处理工程技术研究中心,北京100083 [3]北方工业大学信息学院,北京100144

出　　处：《北京航空航天大学学报》2023年第9期2279-2288,共10页Journal of Beijing University of Aeronautics and Astronautics

基　　金：中央高校基本科研业务费专项资金(BLX202003);国家自然科学基金(61502011);北京林业大学热点追踪项目(BLRD202124)。

摘　　要：在软件故障自动化定位过程中,如果在给定的测试用例集合情况下故障在故障疑似度列表种排名不高,比较有效的方法为补充新的测试用例。如何在较小的代价下提升故障的可疑度排名是一项具有挑战的工作。提出一种基于改进遗传算法(IGA)的测试用例生成方法,利用软件故障定位的疑似故障排名,来辅助生成软件故障定位过程中的测试用例。依次对所提方法进行阐述和分析,在6个C程序和2个Python程序上开展实验,实验结果表明:所提方法自动生成的测试用例能够有效地帮助提高故障定位的效率。The ranking of suspected faults in the process of automatic software fault localization will be continuously created and is determined after the execution of existing test cases.Sometimes the program units corresponding to the fault are ranked lower in the ranking of suspected failures based on the existing test cases.If it is necessary to improve the suspected fault ranking of the program unit corresponding to the fault,supplementary test cases are a feasible method.This article suggests a technique for creating test cases based on a genetic algorithm that can make use of knowledge about the location of software faults.The paper analyzes and analyzes the methods used.Based on the joint experiment of the paper on 6 C programs and 2 Python programs,experimental results show that the test cases automatically generated by this method can effectively help improve the efficiency of fault location.

关 键 词：故障定位 测试用例生成 遗传算法 适应度函数 随机测试 

分 类 号：V221.3[航空宇航科学与技术—飞行器设计] TB553[理学—物理]