Speculative Analysis for Quality Assessment of Code Comments

Rani, Pooja (May 2021). Speculative Analysis for Quality Assessment of Code Comments. In: 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings. Madrid, Spain. May 25 2021 to May 28 2021. 10.1109/ICSE-Companion52605.2021.00132

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Previous studies have shown that high-quality code comments assist developers in program comprehension and maintenance tasks. However, the semi-structured nature of comments, unclear conventions for writing good comments, and the lack of quality assessment tools for all aspects of comments make their evaluation and maintenance a non-trivial problem. To achieve high-quality comments, we need a deeper understanding of code comment characteristics and the practices developers follow. In this thesis, we approach the problem of assessing comment quality from three different perspectives: what developers ask about commenting practices, what they write in comments, and how researchers support them in assessing comment quality. Our preliminary findings show that developers embed various kinds of information in class comments across programming languages. Still, they face problems in locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help developers and researchers in building comment quality assessment tools, we provide: (i) an empirically validated taxonomy of comment convention-related questions from various community forums, (ii) an empirically validated taxonomy of comment information types from various programming languages, (iii) a language-independent approach to automatically identify the information types, and (iv) a comment quality taxonomy prepared from a systematic literature review.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
08 Faculty of Science > Institute of Computer Science (INF) > Software Composition Group (SCG) [discontinued]

UniBE Contributor:

Pooja Rani, Pooja Rani

Subjects:

000 Computer science, knowledge & systems

Language:

English

Submitter:

Oscar Nierstrasz

Date Deposited:

24 Feb 2022 12:10

Last Modified:

02 Mar 2023 23:35

Publisher DOI:

10.1109/ICSE-Companion52605.2021.00132

Uncontrolled Keywords:

comments scg-pub snf-asa3 scg21 jb21

BORIS DOI:

10.48350/165149

URI:

https://boris.unibe.ch/id/eprint/165149

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