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

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楼主: commingle
发表于 2025-3-25 04:15:41 | 显示全部楼层
Using Four-Valued Signal Temporal Logic for Incremental Verification of Hybrid Systemsdict, our verification algorithm is the first to run alongside the reachability analysis of the system to be verified. This makes it possible to stop the reachability analysis as soon as we obtain a conclusive verdict. We demonstrate the usefulness of our novel approach by several experiments.
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Conference proceedings‘‘‘‘‘‘‘‘ 2024Montreal, Canada, during July 24–27, 2024.The primary focus of CAV is to extend the frontiers of verification techniques by expanding to new domains such as security, quantum computing, and machine learning..
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Computing Versal Deformations with Singularm. As a practical realization, we develop an . repair approach. Here, we search for a sequence of repairs that are closer and closer to the original program’s behavior. We implement our method in a prototype and report on encouraging experimental results using off-the-shelf SyGuS solvers.
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Finding Signals in DNA Sequencesrners. This is achieved with, among others, a branch-free implementation of LTL that has . time complexity, where . is trace length, while previous implementations are . or worse (assuming bitwise boolean operations and shifts by powers of 2 have unit costs—a realistic assumption on modern processors).
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Kemin Yu,Min Li,Yang Zhou,Qian Liu – DPSynth – based on these ideas demonstrates that our approach for Boolean realizabilty and synthesis has superior time and space performance over a heuristics-based approach using same symbolic representations. We discuss the advantage on scalability of the new approach, and also investigate our findings on the performance of the DP framework.
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Streaming Adaptive Submodular Maximizationy computing permissive winning strategy templates in finite abstractions of the infinite-state game. The experimental evaluation of our method demonstrates that it outperforms existing techniques and is applicable to infinite-state games beyond the state of the art.
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Dynamic Programming for Symbolic Boolean Realizability and Synthesis – DPSynth – based on these ideas demonstrates that our approach for Boolean realizabilty and synthesis has superior time and space performance over a heuristics-based approach using same symbolic representations. We discuss the advantage on scalability of the new approach, and also investigate our findings on the performance of the DP framework.
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