wielding statistical fault localization statistically

ISCAS OpenIR

	wielding statistical fault localization statistically
	Zhang Yunqian; Chen Lin; Jiang Bo; Zhang Zhenyu
	2012
会议名称	23rd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2012
会议录名称	Proceedings - 23rd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2012
页码	189-194
会议日期	November 27, 2012 - November 30, 2012
会议地点	Dallas, TX, United states
收录类别	EI
ISBN	9780769549286
部门归属	(1) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China; (2) State Key Laboratory for Novel Software Technology Nanjing University Nanjing China; (3) Department of Computer Science Beihang University Beijing China
摘要	Program debugging is a laborious but necessary phase of software development. It generally consists of fault localization, bug fix, and regression testing. Statistical software fault localization automates the manual and error-prone first task. It predicts fault locations by analyzing dynamic program spectrum captured in program runs. Previous studies mostly focused on how to provide reliable input data to such a technique and how to process the data accurately, but inadequately studied how to wield the output result of such a technique. In this work, we raise the assumption of symmetric distribution on the effectiveness of such a technique in locating faults, based on empirical results. We use maximum likelihood estimate and linear programming to develop a tuning method to enhance the result of a statistical fault localization technique. Experiments with two representative such techniques on two realistic UNIX utility programs validate our assumption and show our method effective. © 2012 IEEE.; Program debugging is a laborious but necessary phase of software development. It generally consists of fault localization, bug fix, and regression testing. Statistical software fault localization automates the manual and error-prone first task. It predicts fault locations by analyzing dynamic program spectrum captured in program runs. Previous studies mostly focused on how to provide reliable input data to such a technique and how to process the data accurately, but inadequately studied how to wield the output result of such a technique. In this work, we raise the assumption of symmetric distribution on the effectiveness of such a technique in locating faults, based on empirical results. We use maximum likelihood estimate and linear programming to develop a tuning method to enhance the result of a statistical fault localization technique. Experiments with two representative such techniques on two realistic UNIX utility programs validate our assumption and show our method effective. © 2012 IEEE.
关键词	Maximum Likelihood Estimation Software Reliability Software Testing Technical Presentations
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15819
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Zhang Yunqian,Chen Lin,Jiang Bo,et al. wielding statistical fault localization statistically[C],2012:189-194.