  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
