Article

SMT Sampling via Model-Guided Approximation

Authors:

Matan I. Peled,

Bat-Chen Rothenberg,

Shachar ItzhakyAuthors Info & Claims

Formal Methods: 25th International Symposium, FM 2023, Lübeck, Germany, March 6–10, 2023, Proceedings

Pages 74 - 91

https://doi.org/10.1007/978-3-031-27481-7_6

Published: 06 March 2023 Publication History

Abstract

We investigate the domain of satisfiable formulas in satisfiability modulo theories (SMT), in particular, automatic generation of a multitude of satisfying assignments to such formulas. Despite the long and successful history of SMT in model checking and formal verification, this aspect is relatively under-explored. Prior work exists for generating such assignments, or samples, for Boolean formulas and for quantifier-free first-order formulas involving bit-vectors, arrays, and uninterpreted functions (QF_AUFBV). We propose a new approach that is suitable for a theory T of integer arithmetic and to T with arrays and uninterpreted functions. The approach involves reducing the general sampling problem to a simpler instance of sampling from a set of independent intervals, which can be done efficiently. Such reduction is carried out by expanding a single model—a seed—using top-down propagation of constraints along the original first-order formula.

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Cited By

Yu SLiu ZWang TWang J(2024)Neural Solving Uninterpreted Predicates with Abstract Gradient DescentACM Transactions on Software Engineering and Methodology10.1145/367539433:8(1-47)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3675394
Jia FHan RMa XCui BLiu MHuang PMa FZhang JBissyandé TKlein JBird CSarro F(2023)PSMT: Satisfiability Modulo Theories Meets Probability DistributionProceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE56229.2023.00183(1756-1760)Online publication date: 11-Nov-2023
https://dl.acm.org/doi/10.1109/ASE56229.2023.00183

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Published In

cover image Guide Proceedings

Formal Methods: 25th International Symposium, FM 2023, Lübeck, Germany, March 6–10, 2023, Proceedings

Mar 2023

660 pages

ISBN:978-3-031-27480-0

DOI:10.1007/978-3-031-27481-7

Editors:
Marsha Chechik
University of Toronto, Toronto, ON, Canada
,
Joost-Pieter Katoen
RWTH Aachen University, Aachen, Germany
,
Martin Leucker
University of Lübeck, Lübeck, Germany

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 06 March 2023

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Cited By

Yu SLiu ZWang TWang J(2024)Neural Solving Uninterpreted Predicates with Abstract Gradient DescentACM Transactions on Software Engineering and Methodology10.1145/367539433:8(1-47)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3675394
Jia FHan RMa XCui BLiu MHuang PMa FZhang JBissyandé TKlein JBird CSarro F(2023)PSMT: Satisfiability Modulo Theories Meets Probability DistributionProceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE56229.2023.00183(1756-1760)Online publication date: 11-Nov-2023
https://dl.acm.org/doi/10.1109/ASE56229.2023.00183

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