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• W1783770095 abstract "Transformation-based verification has been proposed to synergistically leverage various transformations to successively simplify and decompose large problems to ones which may be formally discharged. While powerful, such systems require a fair amount of user sophistication and experimentation to yield greatest benefits – every verification problem is different, hence the most efficient transformation flow differs widely from problem to problem. Finding an efficient proof strategy not only enables exponential reductions in computational resources, it often makes the difference between obtaining a conclusive result or not. In this paper, we propose the use of an expert system to automate this proof strategy development process. We discuss the types of rules used by the expert system, and the type of feedback necessary between the algorithms and expert system, all oriented towards yielding a conclusive result with minimal resources. Experimental results are provided to demonstrate that such a system is able to automatically discover efficient proof strategies, even on large and complex problems with more than 100,000 state elements in their respective cones of influence. These results also demonstrate numerous types of algorithmic synergies that are critical to the automation of such complex proofs.KeywordsExpert SystemConclusive ResultPrimary InputProof StrategyBounded Model CheckThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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• W1783770095 date "2004-01-01" @default.
• W1783770095 modified "2023-09-27" @default.
• W1783770095 title "Scalable Automated Verification via Expert-System Guided Transformations" @default.
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• W1783770095 doi "https://doi.org/10.1007/978-3-540-30494-4_12" @default.
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