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Using Statically Computed Invariants Inside the Predicate Abstraction and Refinement Loop

机译:在谓词抽象和细化循环中使用静态计算的不变性

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Predicate abstraction is a powerful technique for extracting finite-state models from often complex source code. This paper reports on the usage of statically computed invariants inside the predicate abstraction and refinement loop. The main idea is to selectively strengthen (conjoin) the concrete transition relation at a given program location by efficiently computed invariants that hold at that program location. We experimentally demonstrate the usefulness of transition relation strengthening in the predicate abstraction and refinement loop. We use invariants of the form ±x±y≤c where c is a constant and x,y are program variables. These invariants can be discovered efficiently at each program location using the octagon abstract domain. We observe that the abstract models produced by predicate abstraction of strengthened transition relation are more precise leading to fewer spurious counterexamples, thus, decreasing the total number of abstraction refinement iterations. Furthermore, the length of relevant fragments of spurious traces needing refinement shortens. This leads to an addition of fewer predicates for refinement. We found a consistent reduction in the total number of predicates, maximum number of predicates tracked at a given program location, and the overall verification time.
机译:谓词抽象是一种从经常复杂的源代码中提取有限状态模型的强大技术。本文报告了谓词抽象和细化循环内部的静态计算不变性的使用。主要思想是通过有效计算在该程序位置的有效计算的不变性,选择性地加强(连on)在给定的程序定位的具体转换关系。我们通过实验展示了谓词抽象和细化环中加强转变关系的有用性。我们使用形式的不变性±x±y≤c,其中c是常数和x,y是程序变量。可以使用OctAgent Abstract域在每个节目位置有效地发现这些不变性。我们观察到通过预加强的过渡关系的谓词抽象制作的抽象模型更加精确,导致杂散的杂散较少,因此降低了抽象精炼迭代的总数。此外,需要细化的虚假迹线的相关碎片的长度缩短。这导致添加更少的细化谓词。我们发现谓词总数,在给定的节目位置跟踪的最大谓词数以及整体验证时间的一致减少。

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