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US08799194B2 Probabilistic model checking of systems with ranged probabilities 有权
具有范围概率的系统概率模型检验

Probabilistic model checking of systems with ranged probabilities
Abstract:
Systems and methods for model checking of live systems are shown that include learning an interval discrete-time Markov chain (IDTMC) model of a deployed system from system logs; and checking the IDTMC model with a processor to determine a probability of violating one or more probabilistic safety properties. Checking the IDTMC model includes calculating a linear part exactly using affine arithmetic; and over-approximating a non-linear part using interval arithmetic.
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