DocumentCode
700371
Title
Detecting duplicate bug reports with software engineering domain knowledge
Author
Aggarwal, Karan ; Rutgers, Tanner ; Timbers, Finbarr ; Hindle, Abram ; Greiner, Russ ; Stroulia, Eleni
Author_Institution
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear
2015
fDate
2-6 March 2015
Firstpage
211
Lastpage
220
Abstract
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.
Keywords
program debugging; software engineering; contextual bug deduplication; contextual word list extraction; duplicate bug report detection; semiautomated method; software engineering domain knowledge; Accuracy; Androids; Computer bugs; Context; Documentation; Feature extraction; Humanoid robots; documentation; duplicate bug reports; information retrieval; machine learning; software engineering textbooks; software literature;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Analysis, Evolution and Reengineering (SANER), 2015 IEEE 22nd International Conference on
Conference_Location
Montreal, QC
Type
conf
DOI
10.1109/SANER.2015.7081831
Filename
7081831
Link To Document