NDLI: CORRECT: code reviewer recommendation at GitHub for Vendasta technologies

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CORRECT: code reviewer recommendation at GitHub for Vendasta technologies

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CORRECT: code reviewer recommendation at GitHub for Vendasta technologies

Content Provider	ACM Digital Library
Author	Roy, Chanchal K. Redl, Jesse Collins, Jason A. Rahman, Mohammad Masudur
Abstract	Peer code review locates common coding standard violations and simple logical errors in the early phases of software development, and thus, reduces overall cost. Unfortunately, at GitHub, identifying an appropriate code reviewer for a pull request is challenging given that reliable information for reviewer identification is often not readily available. In this paper, we propose a code reviewer recommendation tool-CORRECT-that considers not only the relevant cross-project work experience (e.g., external library experience) of a developer but also her experience in certain specialized technologies (e.g., Google App Engine) associated with a pull request for determining her expertise as a potential code reviewer. We design our tool using client-server architecture, and then package the solution as a Google Chrome plug-in. Once the developer initiates a new pull request at GitHub, our tool automatically analyzes the request, mines two relevant histories, and then returns a ranked list of appropriate code reviewers for the request within the browser's context. Demo: https://www.youtube.com/watch?v=rXU1wTD6QQ0 .
Starting Page	792
Ending Page	797
Page Count	6
File Format	PDF
ISBN	9781450338455
DOI	10.1145/2970276.2970283
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Specialized technology experience Cross-project experience Github Code reviewer recommendation Pull request
Content Type	Text
Resource Type	Article

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