Software reliability growth model with change-point and effort control using a power function of the testing time

Abstract

Many software reliability growth models (SRGMs) based on a non-homogenous Poisson process (NHPP) have been developed with the assumption of a constant fault detection rate (FDR) and a fault detection process dependent only on the residual fault content. In this paper we develop a SRGM based on NHPP using a different approach for model development. Here, the fault detection process is dependent not only on the residual fault content, but also on the testing time. It incorporates a realistic situation encountered in software development where the fault detection rate is not constant over the entire testing process, but changes due to variations in resource allocation, defect density, running environment and testing strategy (called the change-point). Here, the FDR is defined as a function of testing time. The proposed model also incorporates the testing effort with the change-point concept which is useful in solving the problems of runaway software projects and provides the testing effort control technique and flexibility to project managers to obtain the desired reliability level. It utilizes failure data collected from software development projects to show its applicability and effectiveness. The statistical package for social sciences (SPSS) based on the least-squares method has been used to estimate unknown parameters. The mean squared error (MSE), relative predictive error (RPE), average mean squared error (AMSE) and the average relative predictive error (ARPE) have been used to validate the model. It is observed that the proposed model results are accurate, highly predictive and incorporate industrial software project concepts.