Robustness of optimum software release policies

In the development of software systems, it is important to determine when the software testing can be stopped and when the system can be released. An optimum release time is usually determined by minimizing the expected total cost under a reliability requirement. Usually the optimum release time depends on the unknown parameters in the underlying reliability growth models and these parameters have to be estimated based on collected testing data. Because of the random nature of the software failure process, there are some problems with the stability of the estimates of model parameters. This makes the conventional procedures for the determination of optimum software release time not robust. Although an extensive literature exists on the problem of software release time determination, few papers address the robustness issue. In this paper, the robustness of optimum release time procedures is studied. The variation of the optimum release time, due to the variation of the estimated parameters, is considered. It is recommended that the optimum release time with its standard error should be taken into consideration. Specifically, the interval estimation of the optimum release time is given for the Goel-Okumoto model and we demonstrate that the robustness can be achieved using interval estimation. Some numerical examples using both real testing data and simulated ones are presented to illustrate the idea.