Article

Probabilistic abstract interpretation

Authors:

Patrick Cousot,

Michael MonerauAuthors Info & Claims

ESOP'12: Proceedings of the 21st European conference on Programming Languages and Systems

Pages 169 - 193

https://doi.org/10.1007/978-3-642-28869-2_9

Published: 24 March 2012 Publication History

Abstract

Abstract interpretation has been widely used for verifying properties of computer systems. Here, we present a way to extend this framework to the case of probabilistic systems.

The probabilistic abstraction framework that we propose allows us to systematically lift any classical analysis or verification method to the probabilistic setting by separating in the program semantics the probabilistic behavior from the (non-)deterministic behavior. This separation provides new insights for designing novel probabilistic static analyses and verification methods.

We define the concrete probabilistic semantics and propose different ways to abstract them. We provide examples illustrating the expressiveness and effectiveness of our approach.

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Wang DReps T(2024)Newtonian Program Analysis of Probabilistic ProgramsProceedings of the ACM on Programming Languages10.1145/36498228:OOPSLA1(305-333)Online publication date: 29-Apr-2024
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Probabilistic abstract interpretation
1. Theory of computation
  1. Semantics and reasoning
    1. Program reasoning

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cover image Guide Proceedings

ESOP'12: Proceedings of the 21st European conference on Programming Languages and Systems

March 2012

599 pages

ISBN:9783642288685

Editor:
Helmut Seidl
Technische Universität München, Boltzmannstrasse 3, Garching, Germany

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 24 March 2012

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Cited By

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https://dl.acm.org/doi/10.1145/3649822
Szekeres DMarussy KMajzik I(2024)A Lazy Abstraction Algorithm for Markov Decision ProcessesAnalytical and Stochastic Modelling Techniques and Applications10.1007/978-3-031-70753-7_6(81-96)Online publication date: 14-Jun-2024
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Parolini FMiné A(2024)Sound Abstract Nonexploitability AnalysisVerification, Model Checking, and Abstract Interpretation10.1007/978-3-031-50521-8_15(314-337)Online publication date: 15-Jan-2024
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Susag ZLahiri SHsu JRoy S(2022)Symbolic execution for randomized programsProceedings of the ACM on Programming Languages10.1145/35633446:OOPSLA2(1583-1612)Online publication date: 31-Oct-2022
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Batz KKaminski BKatoen JMatheja C(2021)Relatively complete verification of probabilistic programs: an expressive language for expectation-based reasoningProceedings of the ACM on Programming Languages10.1145/34343205:POPL(1-30)Online publication date: 4-Jan-2021
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Barthe GChadha RKrogmeier PSistla AViswanathan M(2021)Deciding accuracy of differential privacy schemesProceedings of the ACM on Programming Languages10.1145/34342895:POPL(1-30)Online publication date: 4-Jan-2021
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