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Pervasive contextaware computing networks call for designing algorithms for information propagation and reconfiguration that promote selfadaptation, namely, which can guarantee – at least to a probabilistic extent – certain reliability and robustness properties in spite of unpredicted changes and conditions. The possibility of formally analyzing their properties is obviously an essential engineering requirement, calling for generalpurpose models and tools. As proposed in recent works, several such algorithms can be modeled by the notion of computational field: a dynamically evolving spatial data structure mapping every node of the network to a data value. Based on this idea, as a contribution toward formally verifying properties of pervasive computing systems, in this article we propose a specification language to model computational fields, and a framework based on PRISM stochastic model checker explicitly targeted at supporting temporal property verification. By a number of pervasive computing examples, we show that the proposed approach can be effectively used for quantitative analysis of systems running on networks composed of hundreds of nodes.
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