Path-based calculation of MTTFF, MTTFR, and asymptotic unavailability with the stochastic process algebra tool CASPA

Abstract

CASPA is a stochastic process algebra tool for performance and dependability modelling, analysis, and verification. It is based entirely on the symbolic data structure of the multi-terminal binary decision diagram (MTBDD) which enables the tool to handle models with very large state space. This paper describes an extension of CASPA's solving engine for path-based approximation of the mean time to first failure, the mean time to first recovery, and asymptotic unavailability by MTBDD algorithms. A non-trivial case study illustrates the use of path-based analysis and comparisons between the path-based unavailability calculations and results obtained from standard Markovian analysis are presented.

Implementing dynamic flowgraph methodology models with logic programs

“…This might be based on forward-chaining; 19 however, it is likely that some program transformations 11 would have to be applied to the DFM model of interest first. Future directions in the representation of DFM models in logic programming are related to extending the DFM modeling paradigm by, for example, expressing general time constraints with constraint logic programming, 20 or incorporating elements of process algebra 21 or stochastic activity networks. 22 The framework can be extended in the future to incorporate such central tasks of probabilistic risk analysis as the calculation of importance measures (see Tyrva¨inen and Bjo¨rkman 23 and Karanta 24 ) and uncertainty analysis for DFM models.…”