Abstract
Taking advantage of the naturalness hypothesis for code, recent development, and research has focused on applying machine learning (ML) techniques originally developed for natural language processing (NLP) to drive a new wave of tools and applications aimed specifically for software engineering (SE) tasks. This drive to apply ML and deep learning (DL) has been animated by the large-scale availability of software development data (e.g., source code, code comments, code review comments, commit data, and so on) available from open source platforms such as GitHub and Bitbucket.
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