The Community for Technology Leaders
2014 IEEE International Conference on Software Maintenance and Evolution (ICSME) (2014)
Victoria, BC, Canada
Sept. 29, 2014 to Oct. 3, 2014
ISSN: 1063-6773
ISBN: 978-1-4799-6146-7
pp: 609-612
ABSTRACT
Pull-Request (PR) is the primary method for code contributions from thousands of developers in GitHub. To maintain the quality of software projects, PR review is an essential part of distributed software development. Assigning new PRs to appropriate reviewers will make the review process more effective which can reduce the time between the submission of a PR and the actual review of it. However, reviewer assignment is now organized manually in GitHub. To reduce this cost, we propose a reviewer recommender to predict highly relevant reviewers of incoming PRs. Combining information retrieval with social network analyzing, our approach takes full advantage of the textual semantic of PRs and the social relations of developers. We implement an online system to show how the reviewer recommender helps project managers to find potential reviewers from crowds. Our approach can reach a precision of 74% for top-1 recommendation, and a recall of 71% for top-10 recommendation.
INDEX TERMS
Software, Social network services, Semantics, Software engineering, Conferences, Communities,Distributed Software Development, Pull-request, Reviewer Recommendation, Social Network Analysis
CITATION
Yue Yu, Huaimin Wang, Gang Yin, Charles X. Ling, "Reviewer Recommender of Pull-Requests in GitHub", 2014 IEEE International Conference on Software Maintenance and Evolution (ICSME), vol. 00, no. , pp. 609-612, 2014, doi:10.1109/ICSME.2014.107
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