FDR (fault detection rate), as the key element of reliability research, has great importance in constructing the test environment, improving fault detection efficiency, and modeling and improving reliability. Meantime, it has important practical significance for improving system reliability and determining release time. First, the software reliability growth model SRGM (software reliability growth mode) based on NHPP (non-homogeneous poisson process) is summarized, and the essence, function, and process of modeling are given. Second, based on this, FDR, the key parameter in reliability modeling and researching, is derived, and the definition of it is given. The test environment description ability is analyzed and differences of different models are shown. Third, emphasis is placed on the difference among FDR, failure strength, and hazard rate (risk rate), and then the correlation among the three is derived. Next, the general model of FDR is comprehensively analyzed from three perspectives of test coverage function, FDR set directly, and FDR constituted by testing effort function. Then a unified FDR-related reliability model is proposed. Considering the ability to describe the real test environment, the imperfect debugging framework model is established, and the reliability growth model of multiple different FDRs under imperfect debugging is derived. Further, experiments are carried out on 12 publicly available failure data sets describing real application scenarios to verify the effectiveness of reliability models related to different FDR models, and to analyze and discuss the differences. The results show that the performance of the FDR model can support the performance improvement of the reliability model. Finally, the trend of researches and the problems to be solved are pointed out.