PLBART

Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021.

Note. A detailed documentation is coming soon.

Pre-training data

PLBART is pre-trained on Java and Python functions and natural language descriptions collected from Github and StackOverflow.

Evaluation tasks

We evaluated PLBART on five tasks.

• Code summarization [REF]
• Code generation [REF]
• Code translation [REF]
• Clone detection [REF]
• Vulnerability REF [REF]

Notes

• We will publish the pretrained PLBART checkpoint soon.
• We list all the files in this repository here.

Acknowledgement

PLBART uses Fairseq, codeXglue, and TransCoder and thanks the authors of these works for their contribution.

Citation

@inproceedings{ahmad2020summarization,
    author = {Ahmad, Wasi Uddin and Chakraborty, Saikat and Ray, Baishakhi and Chang, Kai-Wei},
    booktitle = {Proceedings of the 2021 Conference of the North {A}merican Chapter of the Association for Computational Linguistics},
    title = {Unified Pre-training for Program Understanding and Generation},
    year = {2021}
}