Inferring Javascript types using Graph Neural Networks
Jessica Schrouff, Kai Wohlfahrt, Bruno Marnette, Liam P. Atkinson · arXiv (Cornell University) · 2019
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.