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Dynamic stacking ensemble for cross-language code smell detection [PDF]
PeerJ Computer ScienceCode smells refer to poor design and implementation choices by software engineers that might affect the overall software quality. Code smells detection using machine learning models has become a popular area to build effective models that are capable of ...
Hamoud Aljamaan
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Polyglot Code Smell Detection for Infrastructure as Code with GLITCH [PDF]
2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2023 This paper presents GLITCH, a new technology-agnostic framework that enables automated polyglot code smell detection for Infrastructure as Code scripts. GLITCH uses an intermediate representation on which different code smell detectors can be defined. It
Nuno Saavedra +4 more
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SmellyCode++: Multi-Label Dataset for Code Smell Detection [PDF]
Scientific DataContext: Code smells indicate poor software design, affecting maintainability. Accurate detection is vital for refactoring and quality improvement.
Nawaf Alomari +3 more
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FedCSD: A Federated Learning Based Approach for Code-Smell Detection [PDF]
IEEE Access, 2023 Software quality is critical, as low quality, or “Code smell,” increases technical debt and maintenance costs. There is a timely need for a collaborative model that detects and manages code smells by learning from diverse and distributed ...
Sadi Alawadi +6 more
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Machine Learning-Based Methods for Code Smell Detection: A Survey [PDF]
Applied SciencesCode smells are early warning signs of potential issues in software quality. Various techniques are used in code smell detection, including the Bayesian approach, rule-based automatic antipattern detection, antipattern identification utilizing B-splines,
Pravin Singh Yadav +3 more
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Code Smell Detection Using Ensemble Machine Learning Algorithms [PDF]
Applied Sciences, 2022 Code smells are the result of not following software engineering principles during software development, especially in the design and coding phase. It leads to low maintainability.
Seema Dewangan +3 more
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Unsupervised Machine Learning for Effective Code Smell Detection: A Novel Method
Journal of Communications Software and SystemsThe quality of source code is negatively impacted by code smells. Since the term "code smell" originated, numerous attempts have been made to comprehend it by identifying it using various techniques, such as metric-based, heuristic-based, optimization ...
Ruchin Gupta +3 more
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A Novel Approach for Code Smell Detection: An Empirical Study [PDF]
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
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Deep Learning Based Code Smell Detection
IEEE Transactions on Software Engineering, 2021 Code smells are structures in the source code that suggest the possibility of refactorings. Consequently, developers may identify refactoring opportunities by detecting code smells. However, manual identification of code smells is challenging and tedious.
Hui Liu +5 more
semanticscholar +3 more sources
A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique [PDF]
Scientific Reports, 2023 Detecting code smells may be highly helpful for reducing maintenance costs and raising source code quality. Code smells facilitate developers or researchers to understand several types of design flaws. Code smells with high severity can cause significant
Rajwant Singh Rao +3 more
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