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Static Analysis of Programs with Imprecise Probabilistic Inputs

  • Conference paper
Verified Software: Theories, Tools, Experiments (VSTTE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8164))

Abstract

Having a precise yet sound abstraction of the inputs of numerical programs is important to analyze their behavior. For many programs, these inputs are probabilistic, but the actual distribution used is only partially known. We present a static analysis framework for reasoning about programs with inputs given as imprecise probabilities: we define a collecting semantics based on the notion of previsions and an abstract semantics based on an extension of Dempster-Shafer structures. We prove the correctness of our approach and show on some realistic examples the kind of invariants we are able to infer.

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Author information

Authors and Affiliations

  1. CEA LIST, CEA Saclay, 91191, Gif-sur-Yvette CEDEX, France

    Olivier Bouissou, Eric Goubault & Sylvie Putot

  2. LSV, ENS Cachan, 61 avenue du président Wilson, 94230, Cachan, France

    Assale Adje & Jean Goubault-Larrecq

Authors
  1. Assale Adje
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  2. Olivier Bouissou
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  3. Jean Goubault-Larrecq
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  4. Eric Goubault
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  5. Sylvie Putot
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Editor information

Editors and Affiliations

  1. 107 Hewett Road, Wyncote, 19095, PA, USA

    Ernie Cohen

  2. Technische Universität, München, Germany

    Andrey Rybalchenko

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Adje, A., Bouissou, O., Goubault-Larrecq, J., Goubault, E., Putot, S. (2014). Static Analysis of Programs with Imprecise Probabilistic Inputs. In: Cohen, E., Rybalchenko, A. (eds) Verified Software: Theories, Tools, Experiments. VSTTE 2013. Lecture Notes in Computer Science, vol 8164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54108-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-54108-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54107-0

  • Online ISBN: 978-3-642-54108-7

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