2017 # Fair Termination for Parameterized Probabilistic Concurrent Systems

**Abstract:** Abstract. We consider the problem of automatically verifying that a parameterized family of probabilistic concurrent systems terminates with probability one for all instances against adversarial schedulers. A parameterized family defines an infinite-state system: for each number n, the family consists of an instance with n finite-state processes. In contrast to safety, the parameterized verification of liveness is currently still considered extremely challenging especially in the presence of probabilities in t…

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“…Despite our results that SAT-based learning seems to be less efficient than L * learning for synthesising regular inductive invariants in regular model checking, SAT-based learning is more general and more easily applicable when verifying other properties, e.g., liveness [53], fair termination [49], and safety games [57]. View abstraction [5] is a novel technique for parameterised verification.…”

confidence: 78%

“…Despite our results that SAT-based learning seems to be less efficient than L * learning for synthesising regular inductive invariants in regular model checking, SAT-based learning is more general and more easily applicable when verifying other properties, e.g., liveness [53], fair termination [49], and safety games [57]. View abstraction [5] is a novel technique for parameterised verification.…”

confidence: 78%

“…3], [ 31 , threshold-n ]) for the family of predicates for some constant ; two families for threshold predicates of the form [ 8 , 20 ]; and one family for remainder protocols of the form [ 22 ]. Further, we check approximate majority protocols ([ 27 , 56 ], [ 51 , coin game ]). As these protocols only compute the predicate with large probability but not almost surely, we only verify that they always converge to a stable consensus.…”

confidence: 99%

“…Correctness of population protocols is however a liveness property under stochastic schedulers, which choose the agents at random. This distinguishes our work from recent contributions to parameterized verification [38,41].…”

confidence: 94%