Abstract: Abstract:The fault detection rate is one of the main parameters of the software reliability model. Different forms of fault detection rates have different functions. This paper focuses on the impact of fault detection rate on software reliability and proposes two empirical analysis solutions based on information entropy and superi-or-inferior distance decision algorithm: one solution is single-reliability-growth-model single-failure-data-set multi-fault-detection-rate plan and the other is multiple-reliability-growth-model multi-failure-data-set multi-fault-detection-rate. This paper aims to comprehensively analyze the power effect of fault detection rate. According to the experimental analysis, for a single reliability model and a single data set, the impact of failure detection rate on software reliability is mainly related to the failure data set. The performance of different fault detection rates under different data sets is quite different. Under the multiple-data-sets mul-tiple-software-reliability-models situation, the comprehensive performance of the software reliability model corresponding to the power function and the S-type fault detection rate is better, and the comprehensive performance of the software reliability model corresponding to the exponential fault detection rate is poor. The research has a certain guiding role in the selection of parameters in software reliability modeling and the determination of the optimal release time. 

Key words: failure detection rate, reliability modeling, software reliability growth model, empirical analysis