1. A Weighted PageRank-Based Bug Report Summarization Method Using Bug Report Relationships
- Author
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Beomjun Kim, Seonah Lee, and Sungwon Kang
- Subjects
PageRank ,Exploit ,Computer science ,media_common.quotation_subject ,text summarization ,02 engineering and technology ,law.invention ,data-based software engineering ,law ,Reading (process) ,0202 electrical engineering, electronic engineering, information engineering ,General Materials Science ,Quality (business) ,Instrumentation ,media_common ,Fluid Flow and Transfer Processes ,Information retrieval ,Process Chemistry and Technology ,issue tracking system ,General Engineering ,020207 software engineering ,Software maintenance ,Automatic summarization ,Computer Science Applications ,Debugging ,bug report relationships ,020201 artificial intelligence & image processing - Abstract
For software maintenance, bug reports provide useful information to developers because they can be used for various tasks such as debugging and understanding previous changes. However, as they are typically written in the form of conversations among developers, bug reports tend to be unnecessarily long and verbose, with the consequence that developers often have difficulties reading or understanding bug reports. To mitigate this problem, methods that automatically generate a summary of bug reports have been proposed, and various related studies have been conducted. However, existing bug report summarization methods have not fully exploited the inherent characteristics of bug reports. In this paper, we propose a bug report summarization method that uses the weighted-PageRank algorithm and exploits the 'duplicates&rsquo, &lsquo, blocks&rsquo, and &lsquo, depends-on&rsquo, relationships between bug reports. The experimental results show that our method outperforms the state-of-the-art method in terms of both the quality of the summary and the number of applicable bug reports.
- Published
- 2019
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