An S-Shaped Fault Detection and Correction SRGM Subject to Gamma-Distributed Random Field Environment and Release Time Optimization

Abstract

Software system functionality is more crucial, severe, and complex, so we need to predict and quantify the reliability of software in an efficient manner in a random field environment (RFE). But very few researchers consider the RFE in previously proposed software reliability growth models (SRGMs) with fault correction and detection process. In this work, we include both fault correction and detection processes for developing an SRGM in an imperfect debugging environment. We also consider the vagueness of the software fault detection rate in uncertain operating environments. In the recent past, the cost to build a software and its maintenance has become over expenses. Therefore, an optimal release policy would be defined. Proposed analytical model parameters are estimated by least square estimation (LSE) method. Some evaluation criteria like mean square estimation (MSE), coefficient of determination R², adjusted-R², will be calculated for evaluation and compare with some existing models. Sensitive parameters of the model would also be identified. Analysis based on real data shows that the models presented in this paper fit the data more nearly than other previous existing SRGMs.