Pioneering agentic retrieval-augmented generation in software quality: a novel framework for code smell detection via dynamic retrieval
Code smells—subtle indicators of poor design choices—pose significant challenges to software maintainability and readability, particularly in dynamic languages such as Python. Traditional detection methods, including rule-based heuristics and static machine learning classifiers, often suffer from li...
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| Autores principales: | , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
PeerJ Inc.
2026-03-01
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| Colección: | PeerJ Computer Science |
| Materias: | |
| Acceso en línea: | https://peerj.com/articles/cs-3642.pdf |
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