Graph-Augmented Code Summarization in Computational Notebooks
April Wang, Dakuo Wang, Xuye Liu, Lingfei Wu
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.
BibTeX
@inproceedings{ijcai2021p717,
title = {Graph-Augmented Code Summarization in Computational Notebooks},
author = {Wang, April and Wang, Dakuo and Liu, Xuye and Wu, Lingfei},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {5020--5023},
year = {2021},
month = {8},
note = {Demo Track},
doi = {10.24963/ijcai.2021/717},
url = {https://doi.org/10.24963/ijcai.2021/717},
}