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| wielding statistical fault localization statistically | |
| Zhang Yunqian; Chen Lin; Jiang Bo; Zhang Zhenyu | |
| 2012 | |
| Conference Name | 23rd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2012 |
| Source | Proceedings - 23rd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2012 |
| Pages | 189-194 |
| Conference Date | November 27, 2012 - November 30, 2012 |
| Conference Place | Dallas, TX, United states |
| Indexed Type | EI |
| ISBN | 9780769549286 |
| Department | (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 |
| English Abstract | 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. |
| Keyword | Maximum Likelihood Estimation Software Reliability Software Testing Technical Presentations |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15819 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Zhang Yunqian,Chen Lin,Jiang Bo,et al. wielding statistical fault localization statistically[C],2012:189-194. |
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