Microsoft Corporation
Automatic identification of appropriate code reviewers using machine learning

Abstract:

A deep learning model is trained on historical pull requests to automatically identify appropriate reviewers to review source code from one or more source code repositories. The model is trained on features that are based on past pull requests from the source code repositories and that represent the context of the syntactic representation of the changed code. The model learns patterns found in the changed source code and of the past peers associated with the changed source code to relate certain source code fragments with certain peers. The model generates probabilities based on the learned patterns which are used to identify appropriate reviewers more suitable to review the source code.