A unified treatment of three different models concerning the problem of obtaining suitably accurate confidence bounds on series or parallel system reliability from subsystem test data is explored and developed. The component or subsystem test data are assumed to be (1) exponentially distributed with censoring or truncation for a fixed number of failures, (2) exponentially distributed with truncation of tests at fixed times, and (3) binomially distributed (pass-fail) with fixed but different sample sizes and random numbers of failures for subsystem tests. Rather unique relations between the three models are found and discussed based on the binomial reliability study of hlann (1973). In fact, the approximate theory developed herein applies to “mixed” data systems, i.e. the case where some subsystem data are binomial and the others exponential in character. The extension of results to complex systems is also treated. The methodology developed for combining component failure data should perhaps be useful in predicting the reliability performance and the reliability growth of various designs of systems.