A Software Reliability Growth Model Considering Differences Between Testing and Operation

The testing and operation environment may be essentially different, and thus the fault detection rate of testing is different from that of the operation phase. Based on the G-O model, the representative of non-homogeneous Poisson process (NHPP), the fault detection rate from testing to operation is transformed considering the differences of profile of these two phases, and then a more precise NHPP model (TO-SRGM) considering the differences of fault intensity of testing and operation phases is obtained. Finally, the unknown parameters are estimated by the least-squares method based on normalized data set. Experiments show that the goodness-of-fit of the TO-SRGM is better than those of the G-O model and PZ-SRGM on a data set.