RAFF
发表于 2025-3-26 21:17:42
L. Han,L. Rudolph,J. Blumenthal,I. Valodzinprobabilistic and statistical methods in a closed feedback loop with the system’s response. SMLP has been applied in industrial setting at Intel for analyzing and optimizing hardware designs at the analog level. SMLP is a general purpose tool and can be applied to any system that can be sampled and modeled by machine learning models.
vibrant
发表于 2025-3-27 01:20:50
Lecture Notes in Computer Sciencef algebraic methods are used on thousands of automata states, which dramatically amplifies their effect. The merit of this combination of automata with algebraic methods is demonstrated by our prototype implementation being competitive to and even superior to state-of-the-art SMT solvers.
来就得意
发表于 2025-3-27 06:41:54
Muharrem Kılıç,Sezer Bozkuş Kahyaoğlu-based framework for synthesizing refinement lemmas. We extended the state-of-the-art SMT solver Bitwuzla with our abstraction-refinement approach and show that it significantly improves solver performance on a variety of benchmark sets, including industrial benchmarks that arise from smart contract verification.
Carminative
发表于 2025-3-27 10:15:31
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Lobotomy
发表于 2025-3-27 16:01:39
Algebraic Reasoning Meets Automata in Solving Linear Integer Arithmeticf algebraic methods are used on thousands of automata states, which dramatically amplifies their effect. The merit of this combination of automata with algebraic methods is demonstrated by our prototype implementation being competitive to and even superior to state-of-the-art SMT solvers.
抛媚眼
发表于 2025-3-27 20:11:19
Scalable Bit-Blasting with Abstractions-based framework for synthesizing refinement lemmas. We extended the state-of-the-art SMT solver Bitwuzla with our abstraction-refinement approach and show that it significantly improves solver performance on a variety of benchmark sets, including industrial benchmarks that arise from smart contract verification.
神化怪物
发表于 2025-3-27 23:28:36
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hegemony
发表于 2025-3-28 03:30:05
0302-9743 he 36th International Conference on Computer-Aided Verification, CAV 2024, which took place in Montreal, 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 learn
牢骚
发表于 2025-3-28 08:58:53
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可耕种
发表于 2025-3-28 14:06:43
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