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Propagation based local search for bit-precise reasoning
Formal Methods in System Design ( IF 0.7 ) Pub Date : 2017-10-02 , DOI: 10.1007/s10703-017-0295-6
Aina Niemetz , Mathias Preiner , Armin Biere

Many applications of computer-aided verification require bit-precise reasoning as provided by satisfiability modulo theories (SMT) solvers for the theory of quantifier-free fixed-size bit-vectors. The current state-of-the-art in solving bit-vector formulas in SMT relies on bit-blasting, where a given formula is eagerly translated into propositional logic (SAT) and handed to an underlying SAT solver. Bit-blasting is efficient in practice, but may not scale if the input size can not be reduced sufficiently during preprocessing. A recent score-based local search approach lifts stochastic local search from the bit-level (SAT) to the word-level (SMT) without bit-blasting and proved to be quite effective on hard satisfiable instances, particularly in the context of symbolic execution. However, it still relies on brute-force randomization and restarts to achieve completeness. Guided by a completeness proof, we simplified, extended and formalized our propagation-based variant of this approach. We obtained a clean, simple and more precise algorithm that does not rely on score-based local search techniques and does not require brute-force randomization or restarts to achieve completeness. It further yields substantial gain in performance. In this article, we present and discuss our complete propagation based local search approach for bit-vector logics in SMT in detail. We further provide an extended and extensive experimental evaluation including an analysis of randomization effects.

中文翻译:

位精确推理的基于传播的局部搜索

计算机辅助验证的许多应用需要位精确推理,如可满足性模理论 (SMT) 求解器所提供的无量词固定大小位向量理论。当前在 SMT 中求解位向量公式的最新技术依赖于位爆破,其中给定的公式急切地转换为命题逻辑 (SAT) 并交给底层 SAT 求解器。位爆破在实践中是有效的,但如果在预处理期间无法充分减小输入大小,则可能无法扩展。最近的基于分数的局部搜索方法将随机局部搜索从位级 (SAT) 提升到字级 (SMT),无需进行位爆破,并被证明在硬可满足实例上非常有效,特别是在符号执行的上下文中. 然而,它仍然依赖于蛮力随机化并重新启动以实现完整性。在完整性证明的指导下,我们简化、扩展和形式化了这种方法的基于传播的变体。我们获得了一个干净、简单和更精确的算法,它不依赖于基于分数的本地搜索技术,也不需要蛮力随机化或重新启动来实现完整性。它还进一步显着提高了性能。在本文中,我们详细介绍并讨论了 SMT 中位向量逻辑的基于完整传播的局部搜索方法。我们进一步提供了扩展和广泛的实验评估,包括对随机化效果的分析。我们获得了一个干净、简单和更精确的算法,它不依赖于基于分数的本地搜索技术,也不需要蛮力随机化或重新启动来实现完整性。它还进一步显着提高了性能。在本文中,我们详细介绍并讨论了 SMT 中位向量逻辑的基于完整传播的局部搜索方法。我们进一步提供了扩展和广泛的实验评估,包括对随机化效果的分析。我们获得了一个干净、简单和更精确的算法,它不依赖于基于分数的本地搜索技术,也不需要蛮力随机化或重新启动来实现完整性。它还进一步显着提高了性能。在本文中,我们详细介绍并讨论了 SMT 中位向量逻辑的基于完整传播的局部搜索方法。我们进一步提供了扩展和广泛的实验评估,包括对随机化效果的分析。
更新日期:2017-10-02
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