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SubmittedOpen Access (License Unspecified), Open
Conference proceeding
Generating Comments from Source Code with CCGs
PROCEEDINGS OF THE 4TH ACM SIGSOFT INTERNATIONAL WORKSHOP ON NLP FOR SOFTWARE ENGINEERING (NL4SE '18), pp 26-29
01 Jan 2018
Abstract
Good comments help developers understand software faster and provide better maintenance. However, comments are often missing, generally inaccurate, or out of date. Many of these problems can be avoided by automatic comment generation. This paper presents a method to generate informative comments directly from the source code using general-purpose techniques from natural language processing. We generate comments using an existing natural language model that couples words with their individual logical meaning and grammar rules, allowing comment generation to proceed by search from declarative descriptions of program text. We evaluate our algorithm on several classic algorithms implemented in Python.
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Details
- Title
- Generating Comments from Source Code with CCGs
- Creators
- Sergey Matskevich - Drexel UniversityColin S. Gordon - Drexel University
- Contributors
- Y Yu (Editor)E Fredericks (Editor)P Devanbu (Editor)
- Publication Details
- PROCEEDINGS OF THE 4TH ACM SIGSOFT INTERNATIONAL WORKSHOP ON NLP FOR SOFTWARE ENGINEERING (NL4SE '18), pp 26-29
- Publisher
- Assoc Computing Machinery
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000462776100007
- Scopus ID
- 2-s2.0-85061808316
- Other Identifier
- 991019168190504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Software Engineering
- Computer Science, Theory & Methods