Code comment quality analysis and improvement recommendation: An automated approach
Publication Type
Journal Article
Publication Date
8-2016
Abstract
Program comprehension is one of the first and mostfrequently performed activities during software maintenance and evolution. In aprogram, there are not only source code, but also comments. Comments in aprogram is one of the main sources of information for program comprehension. Ifa program has good comments, it will be easier for developers to understand it.Unfortunately, for many software systems, due to developers’ poor coding styleor hectic work schedule, it is often the case that a number of methods andclasses are not written with good comments. This can make it difficult fordevelopers to understand the methods and classes, when they are performingfuture software maintenance tasks. To deal with this problem, in this paper wepropose an approach which assesses the quality of a code comment and generatessuggestions to improve comment quality. A user study is conducted to assess theeffectiveness of our approach and the results show that our comment qualityassessments are similar to the assessments made by our user study participants,the suggestions provided by our approach are useful to improve comment quality,and our approach can improve the accuracy of the previous comment qualityanalysis approaches.
Keywords
Program comprehension, code comment quality analysis, user study
Discipline
Computer Sciences | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
International Journal of Software Engineering and Knowledge Engineering
Volume
26
Issue
6
First Page
981
Last Page
1000
ISSN
0218-1940
Identifier
10.1142/S0218194016500339
Publisher
World Scientific Publishing
Citation
SUN, Xiaobing; GENG, Qiang; David LO; DUAN, Yucong; LIU, Xiangyue; and LI Bin.
Code comment quality analysis and improvement recommendation: An automated approach. (2016). International Journal of Software Engineering and Knowledge Engineering. 26, (6), 981-1000.
Available at: https://ink.library.smu.edu.sg/sis_research/3604
Additional URL
http://doi.org/10.1142/S0218194016500339