Crowdsourced Bug Triaging: Leveraging Q&A Platforms for Bug Assignment

• Author(s) / Creator(s)

  • Badashian, A.S.
  • Hindle, Abram
  • Stroulia, E.

• Bug triaging, i.e., assigning a bug report to the “best” person to address it, involves identifying a list of developers that are qualified to understand and address the bug report, and then ranking them according to their expertise. Most research in this area examines the description of the bug report and the developers’ prior development and bug-fixing activities. In this paper, we propose a novel method that exploits a new source of evidence for the developers’ expertise, namely their contributions in Stack Overflow, the popular software Question and Answer (Q&A) platform. The key intuition of our method is that the questions a developer asks and answers in Stack Overflow, or more generally in software Q&A platforms, can potentially be an excellent indicator of his/her expertise. Motivated by this idea, our method uses the bug-report description as a guide for selecting relevant Stack Overflow contributions on the basis of which to identify developers with the necessary expertise to close the bug under examination. We evaluated this method in the context of the 20 largest GitHub projects, considering 7144 bug reports. Our results demonstrate that our method exhibits superior accuracy to other state-of-the-art methods.

• Date created

  2016

• Subjects / Keywords

  • Stack Overflow
  • GitHub Project
  • Upvotes
  • Multinomial Naive Bayes (MNB)
  • GitHub Users

• Type of Item

  Conference/Workshop Presentation

• DOI

  https://doi.org/10.7939/r3-9n63-jw31

• License

  Attribution 4.0 International