SmellyCode++: Multi-Label Dataset for Code Smell Detection

Abstract Context: Code smells indicate poor software design, affecting maintainability. Accurate detection is vital for refactoring and quality improvement. However, existing datasets often frame detection as single-label classification, limiting realism. Objective: This paper develops a multi-label...

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Bibliographic Details
Main Authors: Nawaf Alomari, Amal Alazba, Hamoud Aljamaan, Mohammad Alshayeb
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05465-z
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