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Horn clause verification with convex polyhedral abstraction and tree automata-based refinement

机译:基于凸多面体抽象和基于树自动机的优化的Horn子句验证

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In this paper we apply tree-automata techniques to refinement of abstract interpretation in Horn clause verification. We go beyond previous work on refining trace abstractions; firstly we handle tree automata rather than string automata and thereby can capture traces in any Horn clause derivations rather than just transition systems; secondly, we show how algorithms manipulating tree automata interact with abstract interpretations, establishing progress in refinement and generating refined clauses that eliminate causes of imprecision. We show how to derive a refined set of Horn clauses in which given infeasible traces have been eliminated, using a recent optimised algorithm for tree automata determinisation. We also show how we can introduce disjunctive abstractions selectively by splitting states in the tree automaton. The approach is independent of the abstract domain and constraint theory underlying the Horn clauses. Experiments using linear constraint problems and the abstract domain of convex polyhedra show that the refinement technique is practical and that iteration of abstract interpretation with tree automata-based refinement solves many challenging Horn clause verification problems. We compare the results with other state-of-the-art Horn clause verification tools. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,我们将树自动机技术应用于Horn子句验证中抽象解释的细化。我们超越了以前的完善跟踪抽象的工作;首先,我们处理树自动机而不是字符串自动机,从而可以捕获任何Horn子句派生中的轨迹,而不仅仅是过渡系统。其次,我们展示了操纵树自动机的算法如何与抽象解释进行交互,如何建立细化的过程并生成消除不精确原因的细化子句。我们展示了如何使用最近优化的树自动机确定算法,推导完善的Horn子句集,其中消除了给定的不可行轨迹。我们还将展示如何通过拆分树自动机中的状态来选择性地引入析取抽象。该方法独立于Horn子句的抽象域和约束理论。使用线性约束问题和凸多面体的抽象域进行的实验表明,改进技术是可行的,并且基于树自动机的优化的抽象解释迭代解决了许多具有挑战性的Horn子句验证问题。我们将结果与其他最新的Horn子句验证工具进行比较。 (C)2015 Elsevier Ltd.保留所有权利。

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