Microsoft Technology Licensing, LLC

Anshul Gupta

Neelakantan Sundaresan

Roshanak Zilouchian Moghaddam

Jason Shaver

Matthew Glenn Jin

Gearard Boland

Payal Bajaj

Eduardo Enrique Noriega De Armas

A code review process utilizes a deep learning model trained on historical code reviews to automatically perform peer or code review of a source code file. The deep learning model is able to predict the code reviews relevant to a source code snippet by learning from historical code reviews. The deep learning model is trained on pairs of code snippets and code reviews that are relevant to each other and pairs of code snippets and code reviews that have no relation to each other. The deep learning model is data driven thereby not relying on pre-configured rules which makes the model adaptable to different review environments.

Data-driven automatic code review

An interactive question and answer (Q&A) service provides pairs of questions and corresponding answers related to the content of a web page. The service includes pre-configured Q&A pairs derived from a deep learning framework that includes a series of neural networks trained through joint and transfer learning to generate questions for a given text passage. In addition, pre-configured Q&A pairs are generated from historical web access patterns and sources related to the content of the web page.

Question and answer pair generation using machine learning

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Kirkland, WA, United States of America

Anshul Gupta