Two different classes of approaches have been suggested for the reliability analysis of multi-phase systems: BDD-based solution approach and Markov chain based approach. These approaches either assume that every phase is static, and thus can be solved with combinatorial methods, or that every phase must be modeled via Markov methods. If every phase is indeed static, then the combinatorial approach is much more efficient than the Markov chain approach. But in a multi-phased system, using currently available techniques, if the failure criteria in even one phase is dynamic, then a Markov approach must be used for every phase. At best this approach is inefficient; at worst it renders solution of multi-phased missions infeasible. In this paper, the authors consider a combination of both approaches, and develop a methodology for combining the analysis of some phases via combinatorial method with the analysis of other phases using Markov methods. The key to this combination is a careful definition of the interfaces and dependencies across phases.
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