Modeling of NHPP-Based SRGM with Two Types of Faults

The various formulations for estimating the reliability of software are relying upon reliability growth models. Such modeling is accomplished furthermore with the consideration that all available faults are instantly detected. During our investigation, faults are labeled into two types based on easiness and difficulty in detection. The Fault detection process (FDP) for two types of faults is explicitly modeled. The applicability of the proposed SRGM is proved using a real dataset. Model parameters are calculated through (LSE) least square estimation, rather the measure of accuracy is the sum of (SSE) squared error,(RMSE) root mean squared error, R-square, and (MSE)mean squared error are evaluated by employing a valid dataset. The estimation with criteria and goodness of fit is also justified.