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International Static Analysis Symposium

SAS 2015: Static Analysis pp 36–53Cite as

A Binary Decision Tree Abstract Domain Functor

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9291))

Abstract

We present an abstract domain functor whose elements are binary decision trees. It is parameterized by decision nodes which are a set of boolean tests appearing in the programs and by a numerical or symbolic abstract domain whose elements are the leaves. We first define the branch condition path abstraction which forms the decision nodes of the binary decision trees. It also provides a new prospective on partitioning the trace semantics of programs as well as separating properties in the leaves. We then discuss our binary decision tree abstract domain functor by giving algorithms for inclusion test, meet and join, transfer functions and extrapolation operators. We think the binary decision tree abstract domain functor may provide a flexible way of adjusting the cost/precision ratio in path-dependent static analysis.

Work supported in part by NSF grant CNS-1446511.

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Notes

  1. 1.

    Note that all examples in this paper are numerical, but this does not mean that our abstract domain functor is limited to numerical abstract domains. Symbolic abstract domains are also allowed.

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Author information

Authors and Affiliations

  1. New York University, New York, USA

    Junjie Chen & Patrick Cousot

Authors
  1. Junjie Chen
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  2. Patrick Cousot
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Corresponding author

Correspondence to Junjie Chen .

Editor information

Editors and Affiliations

  1. Université Rennes 1, Rennes, France

    Sandrine Blazy

  2. Inria, Rennes, France

    Thomas Jensen

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Chen, J., Cousot, P. (2015). A Binary Decision Tree Abstract Domain Functor. In: Blazy, S., Jensen, T. (eds) Static Analysis. SAS 2015. Lecture Notes in Computer Science(), vol 9291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48288-9_3

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  • DOI: https://doi.org/10.1007/978-3-662-48288-9_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48287-2

  • Online ISBN: 978-3-662-48288-9

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