Software Defect Prediction Using an Intelligent Ensemble-Based Model

Software defect prediction plays a crucial role in enhancing software quality while achieving cost savings in testing. Its primary objective is to identify and send only defective modules to the testing stage. This research introduces an intelligent ensemble-based software defect prediction model th...

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Autors principals:	Misbah Ali, Tehseen Mazhar, Yasir Arif, Shaha Al-Otaibi, Yazeed Yasin Ghadi, Tariq Shahzad, Muhammad Amir Khan, Habib Hamam
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2024-01-01
Col·lecció:	IEEE Access
Matèries:	Machine learning software defect prediction ensemble classification heterogeneous classifiers random forest support vector machine
Accés en línia:	https://ieeexplore.ieee.org/document/10413365/
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