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计算机系统应用英文版:2021,30(5):47-58
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基于高阶变异的多错误定位实证研究
(北京化工大学 信息科学与技术学院, 北京 100029)
Empirical Study on Higher Order Mutation-Based Multiple Fault Localization
(College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China)
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Received:September 26, 2020    Revised:October 21, 2020
中文摘要: 错误定位是软件调试中最昂贵的活动之一. 基于变异的错误定位(MBFL)技术假定被大多数失败测试用例杀死的变异体能够很好地定位错误的位置. 之前的研究表明MBFL在单错误定位上有很好的定位效果, 但关于MBFL在多错误定位上的表现没有被深入研究过. 近年来, 高阶变异体被提出用于构造难以被杀死的复杂错误, 但高阶变异体是否能提升MBFL的错误定位精度是未知的. 本文中, 我们研究了一阶变异体和高阶变异体在多错误定位场景下的表现. 进一步, 我们依据不同的变异位置将高阶变异体划分成3类: 准确高阶变异体、部分准确高阶变异体和不准确高阶变异体. 探索哪类变异体在错误定位上更有效. 基于5个程序上的实证研究, 我们发现在多错误定位场景下, 高阶变异体比一阶变异体有更好的定位效果. 更进一步, 我们发现不同种类的高阶变异体的影响是不容忽视的. 具体而言, 准确高阶变异体比不准确高阶变异体有更高的贡献. 因此研究人员应提出更有效的方法生成这类变异体用于未来的MBFL研究.
Abstract:Fault localization is one of the most expensive activities in software debugging.The Mutation-Based Fault Localization (MBFL) assumes that the mutants killed by most of the failed test cases can provide a good indication about the location of a fault. Previous studies showed MBFL could achieve desired results in a Single Fault Localization Scenario (SFL-Scenario), but its performance in a Multiple Fault Localization Scenario (MFL-Scenario) has not been thoroughly evaluated. Recently, Higher Order Mutants (HOMs) have been proposed to model complex faults that are hard to kill, but whether HOMs can improve the performance of MBFL is still unknown. In this study, we investigate the impact of First Order Mutants (FOMs) and HOMs on MBFL in an MFL-Scenario. Moreover, we divide HOMs into three groups, i.e., accurate, partially accurate, and inaccurate HOMs, considering the mutation location in the program, to find which type of HOMs is more efficient in fault localization. Based on the empirical results on five real-world projects, we find that in an MFL-Scenario, HOMs can behave better than FOMs. The influence of the types of HOMs on the effectiveness of MBFL cannot be ignored. In particular, accurate HOMs can contribute more than inaccurate ones. Therefore, researchers should propose effective methods to generate this type of HOMs for future MBFL studies.
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基金项目:国家自然科学基金(62077003, 61902015)
引用文本:
娄琨,尚颖,王海峰.基于高阶变异的多错误定位实证研究.计算机系统应用,2021,30(5):47-58
LOU Kun,SHANG Ying,WANG Hai-Feng.Empirical Study on Higher Order Mutation-Based Multiple Fault Localization.COMPUTER SYSTEMS APPLICATIONS,2021,30(5):47-58