Software development managers and users have been interested in software availability for the software operational phase. It is of great importance to assess software reliability and performance during the operation phase. Therefore, we discuss software availability measurement based on software reliability growth models which describe behavior of software errors detected during the testing and operation phase. These models are formulated by nonhomogeneous Poisson processes (NHPP). The software availability index is defined as the possible system utilization factor which means the percentage of time that the software system will be available for operation. We show numerical examples on software availability measurement for actual software error data.

Many software reliability growth models have been proposed in the last decade, based on software error data observed during testing phase in the software development. However, the existing models are insufficient to represent the time-dependent behavior of testing-effort expenditures in the actual environment of the software testing. For this reason we develop and investigate a testing-effort dependent reliability model incorporating the testing-effort spent on software testing into the software reliability growth. The model is described by a non-homogeneous Poisson process, assuming that the error detection rate to the amount of testing-effort spent at an arbitrary testing time is proportional to the current error content. The time-dependent behavior of testing-effort expenditures is described by a Weibull curve due to the flexibility. From this model, the quantitative software reliability measures are derived. The estimations for the testing-effort parameters and the reliability growth parameters in the model are given by a method of least-squares and by a method of maximum-likelihood, respectively. Then, statistical inferences on the model parameters and the software reliability measures, and analyses of actual software error data and studied.

This paper discusses an optimal software release problem, based on a software reliability growth model incorporating the time-dependent behavior of testing-effort expenditures in the software testing. The problem presents an optimum release time when to stop testing and to be ready for release to the user. In particular, we consider a penalty cost due to delay in the scheduled software delivery time. Using a testing-effort function described a Weibull curve, a software reliability growth process in the error detection phenomenon in software testing is modeled based on a nonhomogeneous Poisson process. The testing-effort parameters and the reliability growth parameters in the model are estimated by a modified least-squares estimation and by a maximum-likelihood estimation, respectively. Based on the software reliability growth mode, the optimal software release problem is formulated by using the total expected software cost to be minimized. Further, numerical examples are presented for illustrations.