We first describe how several existing software reliability growth models based on nonhomogeneous Poisson processes (NHPPs) can be derived based on a unified theory for NHPP models. Under this general framework, we can verify existing NHPP models and derive new NHPP models. The approach covers a number of known models under different conditions. Based on these approaches, we show a method of estimating and computing software reliability growth during the operational phase. We can use this method to describe the transitions from the testing phase to operational phase. That is, we propose a method of predicting the fault detection rate to reflect changes in the user's operational environments. The proposed method offers a quantitative analysis on software failure behavior in field operation and provides useful feedback information to the development process.
['Chin-Yu Huang', 'Sy-Yen Kuo', 'Michael R. Lyu', 'Jung-Hua Lo']
Quantitative software reliability modeling from testing to operation