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| pafl: fault localization via noise reduction on coverage vector | |
| Zhao Lei; Zhang Zhenyu; Wang Lina; Yin Xiaodan | |
| 2011 | |
| Conference Name | SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering |
| Source | SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering |
| Pages | 203-206 |
| Conference Date | July 7, 20 |
| Conference Place | Miami, FL, United states |
| Indexed Type | EI |
| ISBN | 1891706292 |
| Department | (1) Computer School of Wuhan University Key Laboratory of Aerospace Information Security and Trust Computing Wuhan 430072 China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China |
| English Abstract | Coverage-based fault localization techniques assess the extent of how much a program entity relates to faults by contrasting the execution spectra of passed executions and failed executions. However, previous studies show that different test cases may generate similar or identical coverage information in program execution, which makes the execution spectra of program entities indistinguishable to one another, thus involves noise and decreases the effectiveness of existing techniques. In this paper, we use the concept of coverage vector to model program coverage in execution, compare coverage vectors to capture the similarity among test cases, reduce noise by removing similar coverage vector to refine the execution spectra, and based on them assess the suspicious basic blocks being related to fault. We thus narrow down the search region and facilitate fault localization. The empirical evaluation using Siemens programs and realistic UNIX utilities shows that our technique effectively addresses the problem caused by similar test cases and outperforms existing representative techniques.; Coverage-based fault localization techniques assess the extent of how much a program entity relates to faults by contrasting the execution spectra of passed executions and failed executions. However, previous studies show that different test cases may generate similar or identical coverage information in program execution, which makes the execution spectra of program entities indistinguishable to one another, thus involves noise and decreases the effectiveness of existing techniques. In this paper, we use the concept of coverage vector to model program coverage in execution, compare coverage vectors to capture the similarity among test cases, reduce noise by removing similar coverage vector to refine the execution spectra, and based on them assess the suspicious basic blocks being related to fault. We thus narrow down the search region and facilitate fault localization. The empirical evaluation using Siemens programs and realistic UNIX utilities shows that our technique effectively addresses the problem caused by similar test cases and outperforms existing representative techniques. |
| Keyword | Acoustic Noise Measurement Knowledge Engineering Program Debugging Software Engineering Vectors |
| Sponsorship | Knowledge Systems Institute Graduate School |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16262 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Zhao Lei,Zhang Zhenyu,Wang Lina,et al. pafl: fault localization via noise reduction on coverage vector[C],2011:203-206. |
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