A Sensitivity Analysis of a New NHPP Software Reliability Model with the Generalized Exponential Fault Detection Rate Function Considering the Uncertainty of Operating Environments

Early in the development of the software reliability model, it was assumed that the operating environment of the software was used in the same or similar field environment as the test environment. However, they may also be used in many different locations that may differ from the environment in which they were developed and tested. And also, in general, software systems are known to degrade performance and increase failure rate as their service life increases. Therefore, efforts have been made to expand the exponential distribution assuming a constant failure rate. In this paper, we propose a new software reliability model with the generalized exponential (GE) fault detection rate function considering the uncertainty of operation environments based on a non-homogeneous Poisson process (NHPP). We examine the goodness-of-fit of a new NHPP software reliability model and other existing models based on dataset. As a result of comparison of goodness-of-fit, it can be confirmed that the new proposed model is significantly better by showing that all the criteria of the new proposed model are the lowest compared to other models. In addition, the results for the sensitivity analysis show that the parameters of a new NHPP software reliability model affect the mean value function.