CodeStylist: A System for Performing Code Style Transfer Using Neural Networks
DOI:
https://doi.org/10.1609/aaai.v37i13.27087Keywords:
Language Model Probing, Code Style, Generation, CodeT5, Pre-Trained Language Model, PythonAbstract
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.Downloads
Published
2024-07-15
How to Cite
Ting, C.-K., Munson, K., Wade, S., Savla, A., Kate, K., & Srinivas, K. (2024). CodeStylist: A System for Performing Code Style Transfer Using Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16485-16487. https://doi.org/10.1609/aaai.v37i13.27087
Issue
Section
Demonstrations