Titlebook: Computer Aided Verification; 36th International C Arie Gurfinkel,Vijay Ganesh Conference proceedings‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if applica

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Monitizer: Automating Design and?Evaluation of?Neural Network Monitorss if the network’s output is used for decision making in a safety-critical system. Hence, detecting that an input is OOD is crucial for the safe application of the NN. Verification approaches do not scale to practical NNs, making runtime monitoring more appealing for practical use. While various mon

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Madrigal

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Anne Condon,David Harel,Erik Winfree formulas. This abstract domain seems infeasible at first sight due to the complexity of the formulas involved and the enormous size of sets of formulas (abstract elements). We introduce an efficient representation of abstract elements, which eliminates redundancies based on a novel syntactic subsum

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https://doi.org/10.1007/978-3-540-88869-7to their own. These protocols are highly complex and difficult to prove correct. Recently, Bertram, Levinson, and Hsu introduced a language called Slice for describing and verifying cake-cutting protocols. Slice programs can be translated to formulas encoding envy-freeness, which are solved by SMT.

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On Nonuniversal Symport/Antiport P Systemsith respect to the specification. Anticipation is the ability to immediately produce verdicts when the monitor can confidently predict the inevitability of the verdict..Stream runtime verification is a specialized form of runtime verification tailored to the monitoring and verification of data strea

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