Code smells for machine learning applications
Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022 The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applications.
Zhang, H. (author) +2 more
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Research Trends, Detection Methods, Practices, and Challenges in Code Smell: SLR
IEEE Access, 2023 Context: A code smell indicates a flaw in the design, implementation, or maintenance process that could degrade the software’s quality and potentially cause future disruptions.
Muhammad Anis Al Hilmi +5 more
doaj +1 more source
Visualizing Code Bad Smells [PDF]
International Journal of Advanced Computer Science and Applications, 2019 Software visualization is an effective way to support human comprehension to large software systems. In software maintenance, most of the time is spent on understanding code in order to change it. This paper presents a visualization approach to help maintainers to locate and understand code bad smells. Software maintainers need to locate and understand
Maen Hammad, Sabah Alsofriya
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Resource Allocation Modeling Framework to Refactor Software Design Smells [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2023 The domain to study design flaws in the software environment has created enough opportunity for the researchers. These design flaws i.e., code smells, were seen hindering the quality aspects of the software in many ways. Once detected, the segment of the
Priyanka Gupta +2 more
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Exploring the eradication of code smells: An empirical and theoretical perspective [PDF]
, 2010 This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2010 Hindawi Publishing CorporationCode smells reflect code decay, and, as such, developers should seek to eradicate such smells through application of ...
Black, S +4 more
core +3 more sources
Are Smell-Based Metrics Actually Useful in Effort-Aware Structural Change-Proneness Prediction? An Empirical Study [PDF]
, 2019 Bad code smells (also named as code smells) are symptoms of poor design choices in implementation. Existing studies empirically confirmed that the presence of code smells increases the likelihood of subsequent changes (i.e., change-proness).
Jia, Ru +4 more
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Are architectural smells independent from code smells? An empirical study [PDF]
Journal of Systems and Software, 2019 (in press)
Arcelli Fontana F. +3 more
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The effectiveness of refactoring, based on a compatibility testing taxonomy and a dependency graph [PDF]
, 2006 In this paper, we describe and then appraise a testing taxonomy proposed by van Deursen and Moonen (VD&M) based on the post-refactoring repeatability of tests.
Counsell, S +4 more
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Assessment of Code Smell for Predicting Class Change Proneness Using Machine Learning
IEEE Access, 2019 Assessment of code smell for predicting software change proneness is essential to ensure its significance in the area of software quality. While multiple studies have been conducted in this regard, the number of systems studied and the methods used in ...
Nakul Pritam +7 more
doaj +1 more source
A Novel Approach for Code Smell Detection: An Empirical Study
IEEE Access, 2021 Code smells detection helps in improving understandability and maintainability of software while reducing the chances of system failure. In this study, six machine learning algorithms have been applied to predict code smells.
Seema Dewangan +3 more
doaj +1 more source