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Title:
mining associations to improve the effectiveness of fault localization
Author: Zhao Lei ; Wang Li-Na ; Gao Dong-Ming ; Zhang Zhen-Yu ; Xiong Zuo-Ting
Keyword: Hardware ; Software engineering
Source: Jisuanji Xuebao/Chinese Journal of Computers
Issued Date: 2012
Volume: 35, Issue:12, Pages:2528-2540
Indexed Type: EI
Department: (1) Key Laboratory of Aerospace Information Security and Trust Computing Ministry of Education Wuhan 430072 China; (2) School of Computer Wuhan University Wuhan 430072 China; (3) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China
Abstract: Coverage-based fault localization (CBFL) techniques find the fault-related positions in programs by comparing the execution statistics of passed executions and failed executions have been proven to be efficient by several empirical studies. However, these techniques assess the suspiciousness of program entities individually, whereas the individual coverage information cannot reflect the complicated control- and data-dependency relationships, and thus oversimplify the execution spectra. In this paper, we first use motivating examples to show the impact of the cause-effect relationship on the effectiveness of CBFL. Second, we propose the rules of program failures and design the execution analysis model based on the coverage of different program execution spectrum. By computing the frequency items for statements with high suspiciousness, we also bring out the coverage vector to mine fault-prone statements. The controlled experiments based on the SIR benchmarks indicate that our technique is promising.
English Abstract: Coverage-based fault localization (CBFL) techniques find the fault-related positions in programs by comparing the execution statistics of passed executions and failed executions have been proven to be efficient by several empirical studies. However, these techniques assess the suspiciousness of program entities individually, whereas the individual coverage information cannot reflect the complicated control- and data-dependency relationships, and thus oversimplify the execution spectra. In this paper, we first use motivating examples to show the impact of the cause-effect relationship on the effectiveness of CBFL. Second, we propose the rules of program failures and design the execution analysis model based on the coverage of different program execution spectrum. By computing the frequency items for statements with high suspiciousness, we also bring out the coverage vector to mine fault-prone statements. The controlled experiments based on the SIR benchmarks indicate that our technique is promising.
Language: 中文
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/15330
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Zhao Lei,Wang Li-Na,Gao Dong-Ming,et al. mining associations to improve the effectiveness of fault localization[J]. Jisuanji Xuebao/Chinese Journal of Computers,2012-01-01,35(12):2528-2540.
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