Appraising Early Reliability of a Software Component Using Fuzzy Inference

(1) Objectives: Reliability is one of the major aspects for enhancing the operability, reusability, maintainability, and quality of a system. A software component is an independent entity that deploys to form a functional system (CBSS). The component becomes unreliable mainly because of errors introduced during its design and development; it is essential to estimate the reliability of a software component in advance. This research work proposes a novel Mamdani Fuzzy-Inference (M-FIS) model to estimate the components' reliability and provides an intuitive solution for industry personnel; (2) Scope: The technology moves forward from traditional monolithic software development to scalable, integrated, business-driving software applications. Henceforth, the proposed paradigm can give a preliminary estimate of the reliability of software components, and it helps developers and vendors to produce it at high-quality; (3) Methods: In the component development and realization phase, failure data is unavailable; hence, designing metrics, inspections, statistical methods, soft-computing techniques are used to predict early reliability. The present work applies soft computing techniques to validate metrics. Moreover, estimating premature reliability reduces follow-up effort and component-development cost and time; (4) Finding: The proposed model aids the project manager in better estimating and predicting a components' reliability. Adopting both an expert-based fuzzy inference system and an unsupervised, or self-learning, algorithm provides the basis for cross checking, and concludes with a better decision in an ambivalence state.