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Detecting Duplicate Bug Reports with Software Engineering Domain Knowledge

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.

Citation

K. Aggarwal, T. Rutgers, F. Timbers, A. Hindle, R. Greiner, E. Stroulia. "Detecting Duplicate Bug Reports with Software Engineering Domain Knowledge". IEEE International Conference on Software Analysis, Evolution, and Reengineering, pp 211-220, January 2015.

Keywords: duplicate bug reports, information retrieval, software engineering textbooks, machine learning, software literature, documentation
Category: In Conference
Web Links: Proceedings
  DOI

BibTeX

@incollection{Aggarwal+al:SANER15,
  author = {Karan Aggarwal and Tanner Rutgers and Finbarr Timbers and Abram
    Hindle and Russ Greiner and Eleni Stroulia},
  title = {Detecting Duplicate Bug Reports with Software Engineering Domain
    Knowledge},
  Pages = {211-220},
  booktitle = {IEEE International Conference on Software Analysis, Evolution,
    and Reengineering},
  year = 2015,
}

Last Updated: February 11, 2020
Submitted by Sabina P

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