Detecting Duplicate Bug Reports with Software Engineering Domain Knowledge

被引：0
|
作者：
Aggarwal, Karan [1 ]
Rutgers, Tanner [1 ]
Timbers, Finbarr [1 ]
Hindle, Abram [1 ]
Greiner, Russ [1 ]
Stroulia, Eleni [1 ]
机构：
[1] Univ Alberta, Dept Comp Sci, Edmonton, AB, Canada
来源：
2015 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER) | 2015年
关键词：
duplicate bug reports; information retrieval; software engineering textbooks; machine learning; software literature; documentation;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In previous work by Alipour et al., a methodology was proposed for detecting duplicate bug reports by comparing the textual content of bug reports to subject-specific contextual material, namely lists of software-engineering terms, such as non-functional requirements and architecture keywords. When a bug report contains a word in these word-list contexts, the bug report is considered to be associated with that context and this information tends to improve bug-deduplication methods. In this paper, we propose a method to partially automate the extraction of contextual word lists from software-engineering literature. Evaluating this software-literature context method on real-world bug reports produces useful results that indicate this semi-automated method has the potential to substantially decrease the manual effort used in contextual bug deduplication while suffering only a minor loss in accuracy.
引用
收藏
页码：211 / 220
页数：10
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