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

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

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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.

Publication
IEICE TRANSACTIONS on Information Vol.E101-D No.7 pp.1743-1750
Publication Date
2018/07/01
Publicized
2018/04/20
Online ISSN
1745-1361
DOI
10.1587/transinf.2017KBP0016
Type of Manuscript
Special Section PAPER (Special Section on Knowledge-Based Software Engineering)
Category

Authors

Cheng-Zen YANG
  Yuan Ze University
Cheng-Min AO
  Yuan Ze University
Yu-Han CHUNG
  Yuan Ze University

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