Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet, we introduce NLP2Code, a content assist for code snippets. Unlike related tools, NLP2Code integrates directly into the source code editor and provides developers with a content assist feature to close the vocabulary gap between developers' needs and code snippet meta data. Our preliminary evaluation of NLP2Code shows that the majority of invocations lead to code snippets rated as helpful by users and that the tool is able to support a wide range of tasks.
@article{arxiv.1701.05648,
title = {NLP2Code: Code Snippet Content Assist via Natural Language Tasks},
author = {Brock Angus Campbell and Christoph Treude},
journal= {arXiv preprint arXiv:1701.05648},
year = {2017}
}
Comments
tool demo video available at https://www.youtube.com/watch?v=h-gaVYtCznI; to appear as a tool demo paper at ICSME 2017 (https://icsme2017.github.io/)