Bilateral Algorithms for Symbolic Abstraction

  • Aditya Thakur
  • Matt Elder
  • Thomas Reps
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7460)


Given a concrete domain \(\mathcal{C}\), a concrete operation \(\tau: \mathcal{C} \to \mathcal{C}\), and an abstract domain \(\mathcal{A}\), a fundamental problem in abstract interpretation is to find the best abstract transformer \(\tau^{\#}: \mathcal{A} \to \mathcal{A}\) that over-approximates τ. This problem, as well as several other operations needed by an abstract interpreter, can be reduced to the problem of symbolic abstraction: the symbolic abstraction of a formula ϕ in logic \(\mathcal{L}\), denoted by \(\widehat{\alpha}(\varphi)\), is the best value in \(\mathcal{A}\) that over-approximates the meaning of ϕ. When the concrete semantics of τ is defined in \(\mathcal{L}\) using a formula ϕ τ that specifies the relation between input and output states, the best abstract transformer τ # can be computed as \(\widehat{\alpha}(\varphi_\tau)\).

In this paper, we present a new framework for performing symbolic abstraction, discuss its properties, and present several instantiations for various logics and abstract domains. The key innovation is to use a bilateral successive-approximation algorithm, which maintains both an over-approximation and an under-approximation of the desired answer.


Decision Procedure Conjunctive Domain Abstract Domain Galois Connection Cover Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Aditya Thakur
    • 1
  • Matt Elder
    • 1
  • Thomas Reps
    • 1
    • 2
  1. 1.University of WisconsinMadisonUSA
  2. 2.GrammaTech, Inc.IthacaUSA

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