Graph-Augmented Code Summarization in Computational Notebooks
Abstract
Computational notebooks allow data scientists to express their ideas through a combination of code and documentation. However, data scientists often pay attention only to the code and neglect the creation of the documentation in a notebook. In this work, we present a human-centered automation system, Themisto, that can support users to easily create documentation via three approaches: 1) We have developed and reported a GNN-augmented code documentation generation algorithm in a previous paper, which can generate documentation for a given source code; 2) Themisto also implements a query-based approach to retrieve the online API documentation as the summary for certain types of source code; 3) Lastly, Themistoalso enables a user prompt approach to motivate users to write documentation for some use cases that automation does not work well.
Cite
Text
Wang et al. "Graph-Augmented Code Summarization in Computational Notebooks." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/717Markdown
[Wang et al. "Graph-Augmented Code Summarization in Computational Notebooks." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/wang2021ijcai-graph-a/) doi:10.24963/IJCAI.2021/717BibTeX
@inproceedings{wang2021ijcai-graph-a,
title = {{Graph-Augmented Code Summarization in Computational Notebooks}},
author = {Wang, April Yi and Wang, Dakuo and Liu, Xuye and Wu, Lingfei},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2021},
pages = {5020-5023},
doi = {10.24963/IJCAI.2021/717},
url = {https://mlanthology.org/ijcai/2021/wang2021ijcai-graph-a/}
}