Mining Co-location Relationships among Bug Reports to Localize Fault-Prone Modules
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概要
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Automated bug localization is an important issue in software engineering. In the last few decades, various proactive and reactive localization approaches have been proposed to predict the fault-prone software modules. However, most proactive or reactive approaches need source code information or software complexity metrics to perform localization. In this paper, we propose a reactive approach which considers only bug report information and historical revision logs. In our approach, the co-location relationships among bug reports are explored to improve the prediction accuracy of a state-of-the-art learning method. Studies on three open source projects reveal that the proposed scheme can consistently improve the prediction accuracy in all three software projects by nearly 11.6% on average.
- 2010-05-01
著者
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CHEN Ing-Xiang
Department of Computer Science and Engineering, Yuan Ze University
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LI Chien-Hung
Department of Computer Science and Engineering, Yuan Ze University
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YANG Cheng-Zen
Department of Computer Science and Engineering, Yuan Ze University
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Li Chien-hung
Department Of Computer Science And Engineering Yuan Ze University
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Chen Ing-xiang
Department Of Computer Science And Engineering Yuan Ze University
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Yang Cheng-zen
Department Of Computer Science And Engineering Yuan Ze University
関連論文
- Mining Co-location Relationships among Bug Reports to Localize Fault-Prone Modules
- Mining Co-location Relationships among Bug Reports to Localize Fault-Prone Modules