定点方程系统:抽象、博弈、向上技术和局部算法

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2024-10-24 DOI:10.1016/j.ic.2024.105233
Paolo Baldan , Barbara König , Tommaso Padoan
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引用次数: 0

摘要

完整网格上的定点方程系统结合了最小定点和最大定点,经常出现在模型检查和行为等价性检查等验证任务中。在本文中,我们以抽象解释的方式发展了一种近似理论,即把某个具体域上的系统抽象成一个合适的抽象域上的系统,从而确保对解进行合理且可能完整的过度近似。我们还展示了常用于简化共推证明的向上技术如何适合这一抽象解释框架。此外,我们还通过奇偶性博弈来描述定点方程系统的解,从而扩展了之前仅限于连续网格的工作。这种基于博弈的方法允许使用局部算法来验证系统属性,例如确定一个状态是否满足公式或两个状态在行为上是否等价。我们描述了一种局部算法,该算法可与抽象和向上技术相结合,以加快计算速度。
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Systems of fixpoint equations: Abstraction, games, up-to techniques and local algorithms
Systems of fixpoint equations over complete lattices, which combine least and greatest fixpoints, often arise from verification tasks such as model checking and behavioural equivalence checking. In this paper we develop a theory of approximation in the style of abstract interpretation, where a system over some concrete domain is abstracted into a system on a suitable abstract domain, ensuring sound and possibly complete over-approximations of the solutions. We also show how up-to techniques, commonly used to simplify coinductive proofs, fit into this framework, interpreted as abstractions. Additionally, we characterise the solution of fixpoint equation systems through parity games, extending prior work limited to continuous lattices. This game-based approach allows for local algorithms that verify system properties, such as determining whether a state satisfies a formula or two states are behaviourally equivalent. We describe a local algorithm, that can be combined with abstraction and up-to techniques to speed up the computation.
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
期刊最新文献
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