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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ramesh Babu, Merwa
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Computer Science & IT Engineering

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Novel artificial intelligence-based ensemble learning for optimized software quality Govinda, Sangeetha; Vincent, Agnes Nalini; Ramesh Babu, Merwa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp1820-1828

Abstract

Artificial intelligence (AI) contributes towards improving software engineering quality; however, existing AI models are witnessed to deploy learning-based approaches without addressing various complexities associated with datasets. A literature review showcases an unequilbrium between addressing the accuracy and computational burden. Therefore, the proposed manuscript presents a novel AI-based ensemble learning model that is capable of performing an effective prediction of software quality. The presented scheme adopts correlation-based and multicollinearity-based attributes to select essential feature selection. At the same time, the scheme also introduces a hybrid learning approach integrated with a bio-inspired algorithm for constructing the ensemble learning scheme. The quantified outcome of the proposed study showcases 65% minimized defect density, 94% minimized mean time to failure, 62% minimized processing time of the algorithm, and 43% enhanced predictive accuracy.
Co-Authors Govinda, Sangeetha Vincent, Agnes Nalini