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arXiv 2311.03424cs.LOcs.AI
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利用对称性提升可满足性检验

Using Symmetries to Lift Satisfiability Checking

KU Leuven(鲁汶大学);Siemens(西门子);Vrije Universiteit Brussels(布鲁塞尔自由大学)

Pierre Carbonnelle, Gottfried Schenner, Maurice Bruynooghe, Bart Bogaerts, Marc Denecker

AI总结:

本研究提出利用对称性压缩结构的两步可满足性检验方法,为带聚合的带类型一阶逻辑语句设计适配翻译,在生成式配置问题上实现大幅加速,可应用于复杂数据结构软件验证。

摘要:

我们分析了如何利用对称性将结构(也称为解释)压缩到更小的域上且不损失信息。该分析表明,在压缩域中求解可满足性问题有望获得更优性能。为此,我们提出一种两步式新方法:(i)待满足的语句被自动翻译为支持域压缩的“提升”词汇表上的等可满足语句;(ii)通过逐步扩大(初始未知的)压缩域,直到找到满足提升语句的结构,以此检验其可满足性。核心问题在于确保该满足结构总能扩展为满足原始待满足语句的未压缩结构。我们为带聚合的带类型一阶逻辑语句提出了一种合适的翻译方法。实验评估显示,该方法在生成式配置问题上实现了大幅加速,还可应用于处理复杂数据结构的软件验证。我们的结果证明了对对称性约简的语句自动翻译开展进一步研究的合理性。

英文摘要:

We analyze how symmetries can be used to compress structures (also known as interpretations) onto a smaller domain without loss of information. This analysis suggests the possibility to solve satisfiability problems in the compressed domain for better performance. Thus, we propose a 2-step novel method: (i) the sentence to be satisfied is automatically translated into an equisatisfiable sentence over a ``lifted'' vocabulary that allows domain compression; (ii) satisfiability of the lifted sentence is checked by growing the (initially unknown) compressed domain until a satisfying structure is found. The key issue is to ensure that this satisfying structure can always be expanded into an uncompressed structure that satisfies the original sentence to be satisfied. We present an adequate translation for sentences in typed first-order logic extended with aggregates. Our experimental evaluation shows large speedups for generative configuration problems. The method also has applications in the verification of software operating on complex data structures. Our results justify further research in automatic translation of sentences for symmetry reduction.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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