CodeStylist: A System for Performing Code Style Transfer Using Neural Networks

Chih-Kai Ting, Karl Munson, Serenity Wade, Anish Savla, Kiran Kate, Kavitha Srinivas

AAAI 2023 pp. 16485-16487

doi:10.1609/AAAI.V37I13.27087 /aaai/2023/ting2023aaai-codestylist/

Abstract

Code style refers to attributes of computer programs that affect their readability, maintainability, and performance. Enterprises consider code style as important and enforce style requirements during code commits. Tools that assist in coding style compliance and transformations are highly valuable. However, many key aspects of programming style transfer are difficult to automate, as it can be challenging to specify the patterns required to perform the transfer algorithmically. In this paper, we describe a system called CodeStylist which uses neural methods to perform style transfer on code.

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Cite

Text

Ting et al. "CodeStylist: A System for Performing Code Style Transfer Using Neural Networks." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.27087

Markdown

[Ting et al. "CodeStylist: A System for Performing Code Style Transfer Using Neural Networks." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/ting2023aaai-codestylist/) doi:10.1609/AAAI.V37I13.27087

BibTeX

@inproceedings{ting2023aaai-codestylist,
  title     = {{CodeStylist: A System for Performing Code Style Transfer Using Neural Networks}},
  author    = {Ting, Chih-Kai and Munson, Karl and Wade, Serenity and Savla, Anish and Kate, Kiran and Srinivas, Kavitha},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {16485-16487},
  doi       = {10.1609/AAAI.V37I13.27087},
  url       = {https://mlanthology.org/aaai/2023/ting2023aaai-codestylist/}
}