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Title:
pafl: fault localization via noise reduction on coverage vector
Author: Zhao Lei ; Zhang Zhenyu ; Wang Lina ; Yin Xiaodan
Source: SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering
Conference Name: SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering
Conference Date: July 7, 20
Issued Date: 2011
Conference Place: Miami, FL, United states
Keyword: Acoustic noise measurement ; Knowledge engineering ; Program debugging ; Software engineering ; Vectors
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
Sponsorship: Knowledge Systems Institute Graduate School
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.
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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16262
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Zhao Lei,Zhang Zhenyu,Wang Lina,et al. pafl: fault localization via noise reduction on coverage vector[C]. 见:SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering. Miami, FL, United states. July 7, 20.
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