Learning to Fix Build Errors with Graph2Diff Neural Networks

@article{Tarlow2019LearningTF,
  title={Learning to Fix Build Errors with Graph2Diff Neural Networks},
  author={Daniel Tarlow and Subhodeep Moitra and Andrew S C Rice and Zimin Chen and Pierre-Antoine Manzagol and Charles A. Sutton and Edward Aftandilian},
  journal={Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops},
  year={2019}
}
  • Daniel Tarlow, Subhodeep Moitra, +4 authors Edward Aftandilian
  • Published 2019
  • Computer Science, Mathematics
  • Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops
  • Professional software developers spend a significant amount of time fixing builds, but this has received little attention as a problem in automatic program repair. We present a new deep learning architecture, called Graph2Diff, for automatically localizing and fixing build errors. We represent source code, build configuration files, and compiler diagnostic messages as a graph, and then use a Graph Neural Network model to predict a diff. A diff specifies how to modify the code's abstract syntax… CONTINUE READING
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