Titlebook: Computer Aided Verification; 35th International C Constantin Enea,Akash Lal Conference proceedings‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicabl

腐蚀

Systemic Effectiveness Matters,nitor their equipment or device fleets for failures or changes in operation and trigger actions when such events occur. If these models are incorrect, they may become out-of-sync with the actual state of the equipment causing customers to be unable to respond to events occurring on it..Working backw

仇恨

https://doi.org/10.1007/978-3-642-79622-7components. It is essential to address the state explosion problem associated with model checking. However, obtaining the appropriate assumption for AGR is always a highly mental challenge, especially in the case of timed systems. In this paper, we propose a learning-based compositional verification

mitten

Yashwant Kumar M.D., D.N.B.,Alka Bhatia M.D. specification in, e.g., .. The classic STL monitoring is performed by computing a robustness interval that specifies, at each instant, how far the monitored signals are from violating and satisfying the specification. However, since a robustness interval monotonically shrinks during monitoring, cla

Ferritin

https://doi.org/10.1007/978-3-642-71642-3o tell processes apart. The defender-winning initial credits exhaustively determine which preorders and equivalences from the (strong) linear-time–branching-time spectrum relate processes..The time complexity is exponential, which is optimal due to trace equivalence being covered. This complexity im

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APNEA

TIGER

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ensemble

https://doi.org/10.1007/978-3-642-29244-6s that preclude demonic non-determinism, are motivated by practical observations, and are amenable to algorithmic techniques. We provide both logical and stochastic definitions of our fairness notions, and prove that they are equivalent in the context of liveness verification. In particular, we show

BOOST

José Pérez Rios,Xosé Lois Martínez Suárezlly consistent shared memory. In this paper, we first generalize RG to make it parametric with respect to the underlying memory model by introducing an RG framework that is applicable to any model axiomatically characterized by Hoare triples. Second, we instantiate this framework for reasoning about