dynamic-program-embedding

This is the code for our ICLR'18 paper:

• Ke Wang, Rishabh Singh and Zhendong Su, Dynamic Neural Program Embedding for Program Repair, 6th International Conference on Learning Representations, 2018.

Please cite the above paper if you use our code.

The code is released under the MIT license.

Notes

• Training.py constains Variable Trace Model
• StateTraining.py constains State Trace Model
• HybridTraining.py constains Dependency Model
• For all three models, one would have to prepare the input traces for training program. Please refer to the source code for each model on input format. For dependency model a couple of mask tensors are also needed.