Software Reliability Growth Models for the Safety Critical Software with Imperfect Debugging

摘要

In this paper, we will investigate how to perform he log-logistic testing-effort function (TEF) into different software reliability growth models based on non-homogeneous Poisson process (NHPP). The models parameters are estimated by least square estimation (LSE) and maximum likelihood estimation (MLE) methods. The methods of data analysis and comparison criteria are presented and the experimental results from actual data applications are analyzed. Results are compared with the other existing models to show that the proposed models can give fairly better predictions. It is shown that the log-logistic TEF is suitable for incorporating into inflection S-shaped NHPP growth models. In addition, the proposed models are also discussed under imperfect debugging environment.