A holistic approach to software fault prediction with dynamic classification

Software Fault Prediction is a critical domain in machine learning aimed at pre-emptively identifying and mitigating software faults. This study addresses challenges related to imbalanced datasets and feature selection, significantly enhancing the effectiveness of fault prediction models. We mitigat...

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Vydané v:	Automated software engineering Ročník 31; číslo 2; s. 70
Hlavní autori:	Kaliraj, S., Sahasranth, Velisetti Geetha Pavan, Sivakumar, V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.11.2024 Springer Nature B.V
Predmet:	Accuracy Algorithms Artificial Intelligence Computer Science Datasets Decision trees Ensemble learning Fault detection Fault diagnosis Feature extraction Feature recognition Feature selection Machine learning Performance measurement Performance prediction Prediction models Software Software Engineering/Programming and Operating Systems Performance evaluation Ant colony optimization Feature selection Machine learning Dynamic classifier Class-imbalance Software fault prediction Hyperparameter tuning
ISSN:	0928-8910, 1573-7535
On-line prístup:	Získať plný text
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