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Title:
precise propagation of fault-failure correlations in program flow graphs
Author: Zhang Zhenyu ; Chan W.K. ; Tse T.H. ; Jiang Bo
Source: Proceedings - International Computer Software and Applications Conference
Conference Name: 35th Annual IEEE International Computer Software and Applications Conference, COMPSAC 2011
Conference Date: July 18, 2
Issued Date: 2011
Conference Place: Munich, Germany
Keyword: Computer applications ; Electric network analysis
Indexed Type: EI
ISSN: 0730-3157
ISBN: 9780769544397
Department: (1) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China; (2) Department of Computer Science City University of Hong Kong Tat Chee Avenue Hong Kong Hong Kong; (3) Department of Computer Science University of Hong Kong Pokfulam Hong Kong
Sponsorship: IEEE; IEEE Computer Society
Abstract: Statistical fault localization techniques find suspicious faulty program entities in programs by comparing passed and failed executions. Existing studies show that such techniques can be promising in locating program faults. However, coincidental correctness and execution crashes may make program entities indistinguishable in the execution spectra under study, or cause inaccurate counting, thus severely affecting the precision of existing fault localization techniques. In this paper, we propose a BlockRank technique, which calculates, contrasts, and propagates the mean edge profiles between passed and failed executions to alleviate the impact of coincidental correctness. To address the issue of execution crashes, Block-Rank identifies suspicious basic blocks by modeling how each basic block contributes to failures by apportioning their fault relevance to surrounding basic blocks in terms of the rate of successful transition observed from passed and failed executions. BlockRank is empirically shown to be more effective than nine representative techniques on four real-life medium-sized programs. © 2011 IEEE.
English Abstract: Statistical fault localization techniques find suspicious faulty program entities in programs by comparing passed and failed executions. Existing studies show that such techniques can be promising in locating program faults. However, coincidental correctness and execution crashes may make program entities indistinguishable in the execution spectra under study, or cause inaccurate counting, thus severely affecting the precision of existing fault localization techniques. In this paper, we propose a BlockRank technique, which calculates, contrasts, and propagates the mean edge profiles between passed and failed executions to alleviate the impact of coincidental correctness. To address the issue of execution crashes, Block-Rank identifies suspicious basic blocks by modeling how each basic block contributes to failures by apportioning their fault relevance to surrounding basic blocks in terms of the rate of successful transition observed from passed and failed executions. BlockRank is empirically shown to be more effective than nine representative techniques on four real-life medium-sized programs. © 2011 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16224
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Zhang Zhenyu,Chan W.K.,Tse T.H.,et al. precise propagation of fault-failure correlations in program flow graphs[C]. 见:35th Annual IEEE International Computer Software and Applications Conference, COMPSAC 2011. Munich, Germany. July 18, 2.
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