Towards an Improvement of Bug Report Summarization Using Two-Layer Semantic Information

Cheng-Zen YANG  Cheng-Min AO  Yu-Han CHUNG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.7   pp.1743-1750
Publication Date: 2018/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017KBP0016
Type of Manuscript: Special Section PAPER (Special Section on Knowledge-Based Software Engineering)
Category: 
Keyword: 
bug report summarization,  anthropogenic information,  procedural information,  textual information,  semantic model,  

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Summary: 
Bug report summarization has been explored in past research to help developers comprehend important information for bug resolution process. As text mining technology advances, many summarization approaches have been proposed to provide substantial summaries on bug reports. In this paper, we propose an enhanced summarization approach called TSM by first extending a semantic model used in AUSUM with the anthropogenic and procedural information in bug reports and then integrating the extended semantic model with the shallow textual information used in BRC. We have conducted experiments with a dataset of realistic software projects. Compared with the baseline approaches BRC and AUSUM, TSM demonstrates the enhanced performance in achieving relative improvements of 34.3% and 7.4% in the F1 measure, respectively. The experimental results show that TSM can effectively improve the performance.