Detecting duplicate bug reports with software engineering domain knowledge

• Author(s) / Creator(s)

  • Aggarwal, K.
  • Rutgers, T.
  • Timbers, F.
  • Hindle, Abram
  • Greiner, R.
  • Stroulia, E.

• 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.

• Date created

  2015

• Subjects / Keywords

  • duplicate bug reports
  • information retrieval
  • software engineering textbooks
  • machine learning
  • software literature
  • documentation

• Type of Item

  Conference/Workshop Presentation

• DOI

  https://doi.org/10.7939/r3-v9qd-6t35

• License

  Attribution 4.0 International