Dependability assessment is a crucial activity to ensure the correct operation of complex systems. The output of dependability assessment activities include the quantification of reliability, availability, maintenance and safety related metrics. These metrics can assist in the identification of the system weak points or in the conception of mitigation strategies to increase the system dependability level. The development of advanced computer-aided methodologies to support dependability assessment activities is essential to automate and reduce the efforts implied by this process and similarly, the development of accurate dependability assessment methods is very important to increase the quality of the results. In this context, it is possible to identify different contributions that improve the dependability assessment through general-purpose modeling methodologies. However, existing solutions are ad-hoc applications specified with low-level stochastic formalisms and this complicates their adoption in the industry. Accordingly, this paper presents Stochastic Hybrid Fault Tree Automaton (SHyFTA) based simulation algorithm that allows the accurate dependability analysis of repairable multi-state systems. SHyFTA integrates the stochastic and deterministic operation of the system under study as well as their interactions. The algorithm is formalized through an object-oriented software architecture, which is developed as a software library for the modeling and simulation of repairable SHyFTA models. Following the proposed architecture, a Matlab® implementation of this library, SHyFTOO, has been developed and validated with a thorough test campaign. In order to provide a guideline to the end-users and show the potential of the SHyFTOO library, the case study of a feed-water pumping system is implemented in detail and it is used to evaluate different preventive maintenance policies. The SHyFTOO library can open the way to further investigations that address the interactions between the failure behavior and the functional operation of a system and their combined effect on system dependability.
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