Assessment Software Reliability in Component-Based Software Systems: A Comprehensive Review

The reliability of Component-Based Software Systems (CBSS) is a critical factor in the success and longevity of software applications across various domains. This comprehensive review synthesizes methodologies and findings from thirteen key studies, offering a panoramic view of the landscape of CBSS reliability assessment. We explore a spectrum of approaches, from traditional statistical models to advanced computational intelligence techniques, evaluating their effectiveness, challenges, and contexts of applicability. Our review reveals a trend towards the integration of machine learning and fuzzy logic in reliability estimation, reflecting the complexity and dynamic nature of CBSS. Moreover, we identify a significant emphasis on predictive models that cater to early detection of reliability issues, underscoring the proactive aspect of modern software reliability engineering. The findings suggest a need for more adaptable and context-sensitive methods that can accommodate the evolving nature of software components and their interactions. This review not only charts the current state of CBSS reliability assessment but also highlights future directions for research, including the integration of real-time data and the development of more robust models for uncertainty management. Our study serves as a crucial resource for researchers and practitioners seeking to enhance the reliability of CBSS, ultimately contributing to the development of more dependable software systems.