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Solving Horn Clauses on Inductive Data Types Without Induction

机译:在不归纳的情况下解决归纳数据类型的Horn子句

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We address the problem of verifying the satisfiability of Constrained Horn Clauses (CHCs) based on theories of inductively defined data structures, such as lists and trees. We propose a transformation technique whose objective is the removal of these data structures from CHCs, hence reducing their satisfiability to a satisfiability problem for CHCs on integers and booleans. We propose a transformation algorithm and identify a class of clauses where it always succeeds. We also consider an extension of that algorithm, which combines clause transformation with reasoning on integer constraints. Via an experimental evaluation we show that our technique greatly improves the effectiveness of applying the Z3 solver to CHCs. We also show that our verification technique based on CHC transformation followed by CHC solving, is competitive with respect to CHC solvers extended with induction.
机译:我们基于归纳定义的数据结构(如列表和树)的理论,解决了验证约束的Horn子句(CHC)的可满足性的问题。我们提出了一种转换技术,其目标是从CHC中删除这些数据结构,从而将其可满足性降低为CHC对整数和布尔值的可满足性问题。我们提出了一种转换算法,并确定了总是能够成功的一类子句。我们还考虑了该算法的扩展,该算法将子句转换与对整数约束的推理结合在一起。通过实验评估,我们表明我们的技术大大提高了将Z3求解器应用于CHC的有效性。我们还表明,基于CHC转换后再进行CHC求解的验证技术相对于通过归纳扩展的CHC求解器具有竞争力。

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