Hybrid Genetic Algorithm and Machine Learning Approach for Software Reliability Assessment in Safety-Critical Systems
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Software reliability is a paramount determinant of software quality. In this research paper, we delve into utilizing Genetic Algorithms (GAs) for feature selection and classification. We undertake a comprehensive evaluation and comparative analysis of Machine Learning models, specifically Random Forest and Logistic Regression, both with and without Genetic Algorithmdriven feature selection. Our findings substantiate the significant impact of Genetic Algorithms in improving the accuracy of software reliability analysis. © 2024 IEEE.
Description
Keywords
Bio-Optimization, Chi-Squared Statistic, Genetic Algorithms, Logistic Regression, Machine Learning, Model Evaluation, Principal Component Analysis, Random Forest, Software Reliability Analysis
Citation
2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024, 2024, Vol., , p. -