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Cited 2 time in webofscience Cited 5 time in scopus
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A Weighted PageRank-Based Bug Report Summarization Method Using Bug Report Relationshipsopen access

Authors
Kim, BeomjunKang, SungwonLee, Seonah
Issue Date
Dec-2019
Publisher
MDPI
Keywords
data-based software engineering; text summarization; PageRank; issue tracking system; bug report relationships
Citation
APPLIED SCIENCES-BASEL, v.9, no.24
Indexed
SCIE
SCOPUS
Journal Title
APPLIED SCIENCES-BASEL
Volume
9
Number
24
URI
https://scholarworks.bwise.kr/gnu/handle/sw.gnu/8448
DOI
10.3390/app9245427
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', 'blocks', and 'depends-on' 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.
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공과대학 (항공우주및소프트웨어공학부)
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