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Inferring Javascript types using Graph Neural Networks

2019-05-16
Jessica Schrouff, Kai Wohlfahrt, Bruno Marnette, Liam Atkinson

Abstract

The recent use of `Big Code’ with state-of-the-art deep learning methods offers promising avenues to ease program source code writing and correction. As a first step towards automatic code repair, we implemented a graph neural network model that predicts token types for Javascript programs. The predictions achieve an accuracy above $90\%$, which improves on previous similar work.

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URL

https://arxiv.org/abs/1905.06707

PDF

https://arxiv.org/pdf/1905.06707


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