Abstract
The automata-based model checking approach for randomized distributed systems relies on an operational interleaving semantics of the system by means of a Markov decision process (MDP) and a formalization of the desired event E by an ω-regular linear-time property, e.g., an LTL formula. The task is then to compute the greatest lower bound for the probability for E that can be guaranteed even in worst-case scenarios. Such bounds can be computed by a combination of polynomially time-bounded graph algorithm with methods for solving linear programs.
This work was in part funded through the CRC 912 Highly-Adaptive Energy-Efficient Computing (HAEC), the EU under FP7 grant 295261 (MEALS), the DFG/NWO-project ROCKS, the cluster of excellence cfAED (center for Advancing Electronics Dresden) and the DFG project QuaOS.
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Baier, C. (2013). Quantitative Analysis of Randomized Distributed Systems and Probabilistic Automata. In: Muntean, T., Poulakis, D., Rolland, R. (eds) Algebraic Informatics. CAI 2013. Lecture Notes in Computer Science, vol 8080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40663-8_2
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