Supporting the identification of prevalent quality issues in code changes by analyzing reviewers’ feedback

Context: Code reviewers provide valuable feedback during the code review. Identifying common issues described in the reviewers’ feedback can provide input for devising context-specific software development improvements. However, the use of reviewer feedback for this purpose is currently less explore...

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Vydané v:Software quality journal Ročník 33; číslo 2; s. 22
Hlavní autori: Iftikhar, Umar, Börstler, Jürgen, Bin Ali, Nauman, Kopp, Oliver
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.06.2025
Springer Nature B.V
Predmet:
Code changes
Code review
Coherence
Compilers
Computer Science
Computer software selection and evaluation
Context
Data mining
Data Structures and Information Theory
Domain experts
Feedback
Interpreters
Language processing
Maintainability
Modelling
Modern code review
Natural language processing
Natural languages
Open source software
Open source system
Open-source systems
Operating Systems
Programming Languages
Quality
Software design
Software development
Software Engineering/Programming and Operating Systems
Software quality
Software quality improvement
Software quality improvements
Topic Modeling
Modern code review
Open-source systems
Software quality improvement
Natural language processing
ISSN:0963-9314, 1573-1367, 1573-1367
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Popis
Shrnutí:Context: Code reviewers provide valuable feedback during the code review. Identifying common issues described in the reviewers’ feedback can provide input for devising context-specific software development improvements. However, the use of reviewer feedback for this purpose is currently less explored. Objective: In this study, we assess how automation can derive more interpretable and informative themes in reviewers’ feedback and whether these themes help to identify recurring quality-related issues in code changes. Method: We conducted a participatory case study using the JabRef system to analyze reviewers’ feedback on merged and abandoned code changes. We used two promising topic modeling methods (GSDMM and BERTopic) to identify themes in 5,560 code review comments. The resulting themes were analyzed and named by a domain expert from JabRef. Results: The domain expert considered the identified themes from the two topic models to represent quality-related issues. Different quality issues are pointed out in code reviews for merged and abandoned code changes. While BERTopic provides higher objective coherence, the domain expert considered themes from short-text topic modeling more informative and easy to interpret than BERTopic-based topic modeling. Conclusions: The identified prevalent code quality issues aim to address the maintainability-focused issues. The analysis of code review comments can enhance the current practices for JabRef by improving the guidelines for new developers and focusing discussions in the developer forums. The topic model choice impacts the interpretability of the generated themes, and a higher coherence (based on objective measures) of generated topics did not lead to improved interpretability by a domain expert.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0963-9314
1573-1367
1573-1367
DOI:10.1007/s11219-025-09720-9