Software Reliability Growth modeling with Generalized Exponential testing –effort and optimal SOFTWARE RELEASE policy

s In this paper, a scheme for constructing software reliability growth model based on NonHomogeneous Poisson Process is proposed. Although various testing-effort functions for software reliability growth model based on non-homogeneous Poisson process (NHPP) have been proposed. These software reliability growth models are quite helpful for software developers and have been widely accepted and applied by the industry people and by the software developers. We still need to put more testing-effort functions into software reliability growth model for accuracy on estimate of the parameters. In this paper, we will consider the case where the time dependent behaviors of testing-effort expenditures are described by Generalized Exponential Distribution (GED). Software Reliability Growth Models (SRGM) based on the NHPP are developed which incorporates the (GED) testing-effort expenditure during the software-testing phase. It is assumed that the error detection rate to the amount of testing-effort spent during the testing phase is proportional to the current error content. Models parameters are estimated by the Least Square and the Maximum Likelihood estimation methods, and software measures are investigated through numerical experiments on real data from various software projects. The evaluation results are analyzed and compared with other existing models to show that the proposed SRGM with (GED) testing-effort has a fairly and better faults prediction capability and it depicts the real-life situation more fairly. This model can be applied to a wide range of software system. The optimal release policy for this model, based on cost-reliability criterion is also discussed.