Increased efficiency in the quantitative evaluation of state/event fault trees

State/Event Fault Trees (SEFTs) are a new, hierarchical and state-based modelling formalism for dependability analysis. SEFT semantics are defined by mapping the model onto an equivalent Deterministic and Stochastic Petri Net, which is also used for quantitative evaluation. This state-based analysis increases the expressive power of the model but often implies a very large state space. The present paper describes the development of a hybrid approach to avoiding state space largeness in SEFT evaluation. The basic strategy is to minimize model parts that must be evaluated using state-based methods and integrate the partial results in a combinatorial way, based on Binary Decision Diagrams. The approach is implemented in the Fault Tree Analysis framework ESSaRel, which offers SEFTs, among other models, for safety and reliability analysis.