DOI: 10.1007/978-3-540-85845-4_17
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Efficient Hierarchical Reasoning about Functions over Numerical Domains

Abstract: We show that many properties studied in mathematical analysis (monotonicity, boundedness, inverse, Lipschitz properties possibly combined with continuity, derivability) are expressible by formulae in a class for which sound and complete hierarchical proof methods for testing satisfiability of sets of ground clauses exist. The results are useful for automated reasoning in analysis and in the verification of hybrid systems. 1

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Cited by 12 publications
(9 citation statements)
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“…Besides convexity and concavity, other properties are monotonicity properties or boundedness properties. For details we refer to [28]. The equivalence of (2) and (3) in Theorem 3.1 is a locality result for the set of axioms for flows we consider: It states that the universally quantified clauses in the formula Flow q (t 0 , t 1 ), namely:…”
Section: Theorem 35mentioning
confidence: 98%
“…Besides convexity and concavity, other properties are monotonicity properties or boundedness properties. For details we refer to [28]. The equivalence of (2) and (3) in Theorem 3.1 is a locality result for the set of axioms for flows we consider: It states that the universally quantified clauses in the formula Flow q (t 0 , t 1 ), namely:…”
Section: Theorem 35mentioning
confidence: 98%
“…They have proved useful in the verification of parametrized systems [9] and properties of data structures [5,15], and in reasoning about certain properties of numerical functions [14] and functions in ordered domains [16]. Algebraic data types with size functions are shown to be decidable in [19].…”
Section: Related Workmentioning
confidence: 99%
“…is defined, and (3) for every P ∈ Pred: P M = P Theorem 1 (Completability implies extended locality [13] [14]. On the other hand, an extended theory can be extended again, so we can extend T with K 1 , then T ∪ K 1 with K 2 , and so on, if every extension satisfies (Comp w ).…”
Section: Introductionmentioning
confidence: 99%
“…From this partial model, a total model can be constructed as explained in [Sof08]. This model can then be visualized as follows in Mathematica:…”
Section: Model Generation and Visualizationmentioning
confidence: 99%