Inferring Javascript types using Graph Neural Networks

J. Schrouff, K. Wohlfahrt, B. Marnette, L. Atkinson. Representation Learning on Graphs and Manifolds ICLR 2019 workshop 2019

     
GNN types program analysis

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.