CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information
Abstract
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.
Cite
Text
Morishita et al. "CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I21.30575Markdown
[Morishita et al. "CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/morishita2024aaai-chicot/) doi:10.1609/AAAI.V38I21.30575BibTeX
@inproceedings{morishita2024aaai-chicot,
title = {{CHICOT: A Developer-Assistance Toolkit for Code Search with High-Level Contextual Information}},
author = {Morishita, Terufumi and Koreeda, Yuta and Yamaguchi, Atsuki and Morio, Gaku and Imaichi, Osamu and Sogawa, Yasuhiro},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2024},
pages = {23817-23819},
doi = {10.1609/AAAI.V38I21.30575},
url = {https://mlanthology.org/aaai/2024/morishita2024aaai-chicot/}
}