Guiding Developers to Make Informative Commenting Decisions in Source Code

被引：11
|
作者：
Huang, Yuan [1 ]
Jia, Nan [2 ]
Zhou, Qiang [1 ]
Chen, Xiangping [1 ]
Xiong, Yingfei [3 ]
Luo, Xiaonan [1 ]
机构：
[1] Sun Yat Sen Univ, Guangzhou, Guangdong, Peoples R China
[2] Hebei GEO Univ, Shijiazhuang, Hebei, Peoples R China
[3] Peking Univ, Beijing, Peoples R China
来源：
PROCEEDINGS 2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING - COMPANION (ICSE-COMPANION | 2018年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1145/3183440.3194960
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Code commenting is a common programming practice of practical importance to help developers review and comprehend source code. However, there is a lack of thorough specifications to help developers make their commenting decisions in current practice. To reduce the effort of making commenting decisions, we propose a novel method, CommentSuggester, to guide developers regarding appropriate commenting locations in the source code. We extract context information of source code and employ machine learning techniques to identify possible commenting locations in the source code. The encouraging experimental results demonstrated the feasibility and effectiveness of our commenting suggestion method.
引用
收藏
页码：260 / 261
页数：2
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