Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2017
Abstract
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. Video: https://www.youtube.com/watch?v=h-gaVYtCznI
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Proceedings of the 33rd International Conference on Software Maintenance and Evolution, Shanghai, China, 2017 September 17-22
First Page
628
Last Page
632
ISBN
9781538609927
Identifier
10.1109/ICSME.2017.56
Publisher
IEEE
City or Country
Piscataway, NJ
Citation
CAMPBELL, Brock A. and TREUDE, Christoph.
NLP2Code: Code snippet content assist via natural language tasks. (2017). Proceedings of the 33rd International Conference on Software Maintenance and Evolution, Shanghai, China, 2017 September 17-22. 628-632.
Available at: https://ink.library.smu.edu.sg/sis_research/8835
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICSME.2017.56