CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information
DOI:
https://doi.org/10.1609/aaai.v38i21.30575Keywords:
Artificial Intelligence, Intelligent graphical user interfaces, Natural language processing and speech recognition, Systems that integrate different AI technologiesAbstract
We propose a source code search system named CHICOT (Code search with HIgh level COnText) to assist developers in reusing existing code. While previous studies have examined code search on the basis of code-level, fine-grained specifications such as functionality, logic, or implementation, CHICOT addresses a unique mission: code search with high-level contextual information, such as the purpose or domain of a developer's project. It achieves this feature by first extracting the context information from codebases and then considering this context during the search. It provides a VSCode plugin for daily coding assistance, and the built-in crawler ensures up-to-date code suggestions. The case study attests to the utility of CHICOT in real-world scenarios.Downloads
Published
2024-03-24
How to Cite
Morishita, T., Koreeda, Y., Yamaguchi, A., Morio, G., Imaichi, O., & Sogawa, Y. (2024). CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23817-23819. https://doi.org/10.1609/aaai.v38i21.30575
Issue
Section
AAAI Demonstration Track