基于分支执行概率特征选择的故障定位方法

Ang Li, Yan Lei, Xiaoguang Mao
{"title":"基于分支执行概率特征选择的故障定位方法","authors":"Ang Li, Yan Lei, Xiaoguang Mao","doi":"10.1109/QRS.2016.55","DOIUrl":null,"url":null,"abstract":"The current fault localization techniques for debugging basically depend on the binary execution information which indicates each program statement being executed or not executed by a particular test case. However, this simple information may lose some essential clues such as the branching execution information for fault localization, and therefore restricts localization effectiveness. To alleviate this problem, this paper proposes a novel fault localization approach denoted as FLBF which incorporates the branching execution information in the manner of feature selection. This approach firstly uses branching execution probability to model the behavior of each statement as a feature, then adopts one of the most widely used feature selection method called Fisher score to calculate the relevance between each statement's feature and the failures, and finally outputs the suspicious statements potentially responsible for the failures. The scenario used to demonstrate the utility of FLBF is composed of two standard benchmarks and three real-life UNIX utility programs. The experimental results show that input with branching execution information can improve the performance of current fault localization techniques and FLBF performs more stably and efficiently than other six typical fault localization techniques.","PeriodicalId":412973,"journal":{"name":"2016 IEEE International Conference on Software Quality, Reliability and Security (QRS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Towards More Accurate Fault Localization: An Approach Based on Feature Selection Using Branching Execution Probability\",\"authors\":\"Ang Li, Yan Lei, Xiaoguang Mao\",\"doi\":\"10.1109/QRS.2016.55\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current fault localization techniques for debugging basically depend on the binary execution information which indicates each program statement being executed or not executed by a particular test case. However, this simple information may lose some essential clues such as the branching execution information for fault localization, and therefore restricts localization effectiveness. To alleviate this problem, this paper proposes a novel fault localization approach denoted as FLBF which incorporates the branching execution information in the manner of feature selection. This approach firstly uses branching execution probability to model the behavior of each statement as a feature, then adopts one of the most widely used feature selection method called Fisher score to calculate the relevance between each statement's feature and the failures, and finally outputs the suspicious statements potentially responsible for the failures. The scenario used to demonstrate the utility of FLBF is composed of two standard benchmarks and three real-life UNIX utility programs. The experimental results show that input with branching execution information can improve the performance of current fault localization techniques and FLBF performs more stably and efficiently than other six typical fault localization techniques.\",\"PeriodicalId\":412973,\"journal\":{\"name\":\"2016 IEEE International Conference on Software Quality, Reliability and Security (QRS)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Software Quality, Reliability and Security (QRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QRS.2016.55\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Software Quality, Reliability and Security (QRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QRS.2016.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

当前用于调试的故障定位技术基本上依赖于二进制执行信息,该信息表明特定测试用例正在执行或未执行每个程序语句。但是,这种简单的信息可能会丢失一些重要的线索,例如故障定位的分支执行信息,从而限制了定位的有效性。为了解决这一问题,本文提出了一种新的故障定位方法,即FLBF,该方法以特征选择的方式结合了分支执行信息。该方法首先利用分支执行概率将每条语句的行为建模为特征,然后采用最常用的一种特征选择方法Fisher score来计算每条语句的特征与故障之间的相关性,最后输出可能导致故障的可疑语句。用于演示FLBF实用程序的场景由两个标准基准测试和三个实际的UNIX实用程序组成。实验结果表明,带有分支执行信息的输入可以提高现有故障定位技术的性能,FLBF比其他六种典型故障定位技术性能更稳定、更高效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards More Accurate Fault Localization: An Approach Based on Feature Selection Using Branching Execution Probability
The current fault localization techniques for debugging basically depend on the binary execution information which indicates each program statement being executed or not executed by a particular test case. However, this simple information may lose some essential clues such as the branching execution information for fault localization, and therefore restricts localization effectiveness. To alleviate this problem, this paper proposes a novel fault localization approach denoted as FLBF which incorporates the branching execution information in the manner of feature selection. This approach firstly uses branching execution probability to model the behavior of each statement as a feature, then adopts one of the most widely used feature selection method called Fisher score to calculate the relevance between each statement's feature and the failures, and finally outputs the suspicious statements potentially responsible for the failures. The scenario used to demonstrate the utility of FLBF is composed of two standard benchmarks and three real-life UNIX utility programs. The experimental results show that input with branching execution information can improve the performance of current fault localization techniques and FLBF performs more stably and efficiently than other six typical fault localization techniques.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信