A hybrid bug triage algorithm for developer recommendation

Tao Zhang, Byungjeong Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

43 Scopus citations


With a great number of software applications that have been developed, software maintenance has become an important and challenging task, particularly due to the increasing scale of software projects. Even if developers can create and update bug reports in bug repositories to support software maintenance, a large software project receives a large number of bug reports each day. For reducing the workload of developers, many researchers and software engineers have begun recommending appropriate developers to fix bugs. This process is called bug triage and is a hot research topic for software maintenance. In this paper, we propose a hybrid bug triage algorithm, combining a probability model and an experience model to rank all candidate developers for fixing a new bug. For this study, we adopted the smoothed Unigram Model (UM) instead of the traditional Vector Space Model (VSM) to search similar bug reports. In the probability model, we used a social network to analyze the probability of fixing a new bug for a candidate developer. We first proposed to add a new feature (the number of re-opened bugs) in order to get the fixing probability. In the experience model, we considered the number of fixed bugs and fixing cost for each candidate developer as the estimate factor. In addition, we introduced a new concept, activity factor, to better model developers' experience. We performed the experiments on two large-scale, open source projects. The results show that our method can effectively recommend the best developer for fixing bugs.

Original languageEnglish
Title of host publication28th Annual ACM Symposium on Applied Computing, SAC 2013
Number of pages7
StatePublished - 2013
Event28th Annual ACM Symposium on Applied Computing, SAC 2013 - Coimbra, Portugal
Duration: 18 Mar 201322 Mar 2013

Publication series

NameProceedings of the ACM Symposium on Applied Computing


Conference28th Annual ACM Symposium on Applied Computing, SAC 2013


  • Bug triage
  • Experience model
  • Probability model
  • Smoothed Unigram Model
  • Social network


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