NHPP-Based Testing Coverage model with Fault Removal Efficiency and Error Generation
Javaid Iqbal, Rabia Nazir, Tariq Rasool · International Journal of Reliability Quality and Safety Engineering · 2024
This paper introduces an innovative approach aimed at enhancing software reliability by integrating testing coverage within a nonhomogeneous Poisson process (NHPP). The reliability of software holds paramount significance for both developers and users, hinging on precise reliability estimations. In this paper, three real-world datasets are used to examine goodness-of-fit of the proposed model and the performance is compared with 11 other existing NHPP models. The performance of all the models is evaluated using five goodness-of-fit criteria including mean square error (MSE), Akaike’s information criterion (AIC), Bayesian information criterion (BIC), predictive risk ratio (PRR) and Pham’s criterion (PC). The results reveal that, when it comes to predictive power and goodness-of-fit, our proposed model surpasses the other models.