Towards an Intelligent Code Search Engine

Abstract

Software developers increasingly rely on information from the Web, such as documents or code examples on Application Programming Interfaces (APIs), to facilitate their development processes. However, API documents often do not include enough information for developers to fully understand the API usages, while searching for good code examples requires non-trivial efforts. To address this problem, we propose a novel code search engine, combining the strength of browsing documents and searching for code examples, by returning documents embedded with high-quality code example summaries mined from the Web. Our evaluation results show that our approach provides code examples with high precision and boosts programmer productivity.

Cite

Text

Kim et al. "Towards an Intelligent Code Search Engine." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7503

Markdown

[Kim et al. "Towards an Intelligent Code Search Engine." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/kim2010aaai-intelligent/) doi:10.1609/AAAI.V24I1.7503

BibTeX

@inproceedings{kim2010aaai-intelligent,
  title     = {{Towards an Intelligent Code Search Engine}},
  author    = {Kim, Jinhan and Lee, Sanghoon and Hwang, Seung-won and Kim, Sunghun},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2010},
  pages     = {1358-1363},
  doi       = {10.1609/AAAI.V24I1.7503},
  url       = {https://mlanthology.org/aaai/2010/kim2010aaai-intelligent/}
}