Assessment of Code Smell for Predicting Class Change Proneness Using Machine Learning

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 this paper are quite different, thus, causing co...

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Autors principals:	Nakul Pritam, Manju Khari, Le Hoang Son, Raghvendra Kumar, Sudan Jha, Ishaani Priyadarshini, Mohamed Abdel-Basset, Hoang Viet Long
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2019-01-01
Col·lecció:	IEEE Access
Matèries:	Code smell change proneness software maintenance machine learning multilayer perceptron
Accés en línia:	https://ieeexplore.ieee.org/document/8667419/
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