The testing and operation environments may be essentially different, thus the fault detection rate (FDR) of testing phase is different from that of the operation phase. In this paper, based on the representative model, G-O model, of nonhomogeneous Poisson Process (NHPP), a transformation is performed between the FDR of the testing phase to that of the operation considering the profile differences of the two phases, and then a software reliability growth model (SRGM) called TO-SRGM describing the differences of the FDR between the testing phase and the operation phase is proposed. Finally, the parameters of the model are estimated using the least squares estimate (LSE) based on normalized failure data. Experiment results show that the goodness-of-fit of the TO-SRGM is better than that of the G-O model and the PZ-SRGM on the normalized failure data set.