Abstract-Sound criteria for partial order reduction for probabilistic concurrent systems have been presented in the literature. Their realization relies on a depth-first search-based approach for generating the reduced model. The drawback of this dynamic approach is that it can hardly be combined with other techniques to tackle the state explosion problem, e.g., symbolic probabilistic model checking with multi-terminal variants of binary decision diagrams. Following the approach presented by Kurshan et al. for non-probabilistic systems, we study partial order reduction techniques for probabilistic concurrent systems that can be realized by a static analysis. The idea is to inject the reduction criteria into the control flow graphs of the processes of the system to be analyzed. We provide the theoretical foundations of static partial order reduction for probabilistic concurrent systems and present algorithms to realize them. Finally, we report on some experimental results. The state space explosion problem is known to be one of the major limitations for the application of model checking as a formal verification technique for complex systems. Even for finite-state abstractions the exploration of the full state space of a system model M can be intractable due to computational and storage restrictions. Along the years, several approaches have been proposed to ease this problem, e.g. symbolic model checking [1] , where the verification process does not deal with states individually but with groups of them. This symbolic approach is known to outperform enumerative approaches, also known as explicit model checking, in terms of the size of the state spaces that can be verified. Other techniques that try to alleviate state space explosion are known as partial order reductions (POR), see e.g. . These techniques try to avoid the generation of the complete state space of a system model M by identifying redundant interleavings and generate a reduced system model with fewer transitions and states. The rough idea is to use the commutativity of independent actions and to ensure that the reduced model covers all possible behaviors of the full model up to permutations of independent actions. There are several desirable conditions for the reduced modelM. First of all, the partial order reduction techniques should be propertypreserving, which means that M |= φ if and only ifM |= φ
In the context of Markov Decision Processes (MDP) partial order reduction techniques have been explored to obtain state space reduction REF .
Static Partial Order Reduction for Probabilistic Concurrent Systems
2012 Ninth International Conference on Quantitative Evaluation of Systems
2012 Ninth International Conference on Quantitative Evaluation of Systems
Computer Science