Proceedings

Graph-Augmented Code Summarization in Computational Notebooks

Download BibTeX Cite

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Demo Track. Pages 5020-5023.

https://doi.org/10.24963/ijcai.2021/717

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.

April Wang, Dakuo Wang, Xuye Liu, and Lingfei Wu. 2021. Graph-Augmented Code Summarization in Computational Notebooks. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 5020–5023. https://doi.org/10.24963/ijcai.2021/717
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards