CodeStylist: A System for Performing Code Style Transfer Using Neural Networks
Keywords:Language Model Probing, Code Style, Generation, CodeT5, Pre-Trained Language Model, Python
AbstractCode 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.
How to Cite
Ting, C.-K., Munson, K., Wade, S., Savla, A., Kate, K., & Srinivas, K. (2023). 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