Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-26598
Publication type: | Article in scientific journal |
Type of review: | Peer review (publication) |
Title: | A decade of code comment quality assessment : a systematic literature review |
Authors: | Rani, Pooja Blasi, Arianna Stulova, Nataliia Panichella, Sebastiano Gorla, Alessandra Nierstrasz, Oscar |
et. al: | No |
DOI: | 10.1016/j.jss.2022.111515 10.21256/zhaw-26598 |
Published in: | Journal of Systems and Software |
Volume(Issue): | 195 |
Issue: | 111515 |
Issue Date: | 2023 |
Publisher / Ed. Institution: | Elsevier |
ISSN: | 0164-1212 1873-1228 |
Language: | English |
Subjects: | Code comment; Documentation quality; Systematic literature review |
Subject (DDC): | 005: Computer programming, programs and data |
Abstract: | Code comments are important artifacts in software systems and play a paramount role in many software engineering (SE) tasks related to maintenance and program comprehension. However, while it is widely accepted that high quality matters in code comments just as it matters in source code, assessing comment quality in practice is still an open problem. First and foremost, there is no unique definition of quality when it comes to evaluating code comments. The few existing studies on this topic rather focus on specific attributes of quality that can be easily quantified and measured. Existing techniques and corresponding tools may also focus on comments bound to a specific programming language, and may only deal with comments with specific scopes and clear goals (e.g., Javadoc comments at the method level, or in-body comments describing TODOs to be addressed). In this paper, we present a Systematic Literature Review (SLR) of the last decade of research in SE to answer the following research questions: (i) What types of comments do researchers focus on when assessing comment quality? (ii) What quality attributes (QAs) do they consider? (iii) Which tools and techniques do they use to assess comment quality?, and (iv) How do they evaluate their studies on comment quality assessment in general? Our evaluation, based on the analysis of 2353 papers and the actual review of 47 relevant ones, shows that (i) most studies and techniques focus on comments in Java code, thus may not be generalizable to other languages, and (ii) the analyzed studies focus on four main QAs of a total of 21 QAs identified in the literature, with a clear predominance of checking consistency between comments and the code. We observe that researchers rely on manual assessment and specific heuristics rather than the automated assessment of the comment quality attributes, with evaluations often involving surveys of students and the authors of the original studies but rarely professional developers. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/26598 |
Fulltext version: | Published version |
License (according to publishing contract): | CC BY-NC-ND 4.0: Attribution - Non commercial - No derivatives 4.0 International |
Departement: | School of Engineering |
Organisational Unit: | Institute of Computer Science (InIT) |
Published as part of the ZHAW project: | COSMOS – DevOps for Complex Cyber-physical Systems of Systems |
Appears in collections: | Publikationen School of Engineering |
Files in This Item:
File | Description | Size | Format | |
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2023_Rani-etal_Code-comment-quality-assessment-literature-review_JSS.pdf | 1.87 MB | Adobe PDF | View/Open |
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Rani, P., Blasi, A., Stulova, N., Panichella, S., Gorla, A., & Nierstrasz, O. (2023). A decade of code comment quality assessment : a systematic literature review. Journal of Systems and Software, 195(111515). https://doi.org/10.1016/j.jss.2022.111515
Rani, P. et al. (2023) ‘A decade of code comment quality assessment : a systematic literature review’, Journal of Systems and Software, 195(111515). Available at: https://doi.org/10.1016/j.jss.2022.111515.
P. Rani, A. Blasi, N. Stulova, S. Panichella, A. Gorla, and O. Nierstrasz, “A decade of code comment quality assessment : a systematic literature review,” Journal of Systems and Software, vol. 195, no. 111515, 2023, doi: 10.1016/j.jss.2022.111515.
RANI, Pooja, Arianna BLASI, Nataliia STULOVA, Sebastiano PANICHELLA, Alessandra GORLA und Oscar NIERSTRASZ, 2023. A decade of code comment quality assessment : a systematic literature review. Journal of Systems and Software. 2023. Bd. 195, Nr. 111515. DOI 10.1016/j.jss.2022.111515
Rani, Pooja, Arianna Blasi, Nataliia Stulova, Sebastiano Panichella, Alessandra Gorla, and Oscar Nierstrasz. 2023. “A Decade of Code Comment Quality Assessment : A Systematic Literature Review.” Journal of Systems and Software 195 (111515). https://doi.org/10.1016/j.jss.2022.111515.
Rani, Pooja, et al. “A Decade of Code Comment Quality Assessment : A Systematic Literature Review.” Journal of Systems and Software, vol. 195, no. 111515, 2023, https://doi.org/10.1016/j.jss.2022.111515.
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