Empirical Analysis of Data Sampling-Based Decision Forest Classifiers for Software Defect Prediction

Empirical Analysis of Data Sampling-Based Decision Forest Classifiers for Software Defect Prediction

The strategic significance of software testing in ensuring the success of software development projects is paramount. Comprehensive testing, conducted early and consistently across the development lifecycle, is vital for mitigating defects, especially given the constraints on time, budget, and other...

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Main Authors: Fatima Enehezei Usman-Hamza, Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz, Shuib Basri, Rafiat Ajibade Oyekunle, Hammed Adeleye Mojeed, Abimbola Ganiyat Akintola
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Software
Subjects:
software defect prediction
data sampling
tree classifiers
decision forest
Online Access:https://www.mdpi.com/2674-113X/4/2/7
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