Journal ArticleDOI
Quantifying the Effect of Code Smells on Maintenance Effort
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TLDR
To reduce maintenance effort, a focus on reducing code size and the work practices that limit the number of changes may be more beneficial than refactoring code smells.Abstract:
Context: Code smells are assumed to indicate bad design that leads to less maintainable code. However, this assumption has not been investigated in controlled studies with professional software developers. Aim: This paper investigates the relationship between code smells and maintenance effort. Method: Six developers were hired to perform three maintenance tasks each on four functionally equivalent Java systems originally implemented by different companies. Each developer spent three to four weeks. In total, they modified 298 Java files in the four systems. An Eclipse IDE plug-in measured the exact amount of time a developer spent maintaining each file. Regression analysis was used to explain the effort using file properties, including the number of smells. Result: None of the 12 investigated smells was significantly associated with increased effort after we adjusted for file size and the number of changes; Refused Bequest was significantly associated with decreased effort. File size and the number of changes explained almost all of the modeled variation in effort. Conclusion: The effects of the 12 smells on maintenance effort were limited. To reduce maintenance effort, a focus on reducing code size and the work practices that limit the number of changes may be more beneficial than refactoring code smells.read more
Citations
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Proceedings ArticleDOI
An Empirical Study of Long Method and God Method in Industrial Projects
TL;DR: The study highlights the need for a clearer definition of this kind of code smell, and there are many factors not only length which is affecting the code quality, and at the same time the definition of "doing too much" should be modeling to illuminate this kindof code smell.
Journal ArticleDOI
Code Smells in Machine Learning Systems
Jiri Gesi,Siqi Liu,Jiawei Li,Iftekhar Ahmed,Nachi Nagappan,David Lo,Eduardo Santana de Almeida,Pavneet Singh Kochhar,Lingfeng Bao +8 more
TL;DR: This is the first study on investigating code smells in the context of DL software systems, which helps researchers and practitioners to get a first look at what kind of maintenance modification made and what code smells developers have been dealing with.
On Continuous Detection of Design Flaws in Evolving Object-Oriented Programs using Incremental Multi-Pattern Matching.
TL;DR: In this article, a comprehensive methodology for specifying object-oriented design flaws by means of compound rules integrating code metrics, code smells and anti-patterns in a modular way is proposed.
Proceedings ArticleDOI
An Empirical Study on Maintainable Method Size in Java
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Proceedings ArticleDOI
Alternative Sources of Information for Code Smell Detection: Postcards from Far Away
TL;DR: This work highlights several aspects that can possibly contribute to the improvement of the current state of the art of code smell detection and proposes solutions, based on the analysis on how code smells are actually introduced as well as the usefulness of historical and textual information to realize more reliable code smell detectors.
References
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Journal ArticleDOI
A Systematic Literature Review on Fault Prediction Performance in Software Engineering
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Journal ArticleDOI
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