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Model Generation for Quantified Formulas: A Taint-Based Approach

Benjamin Farinier 1, 2 Sébastien Bardin 1 Richard Bonichon 1 Marie-Laure Potet 2 
1 LSL - Laboratoire Sûreté des Logiciels
DILS - Département Ingénierie Logiciels et Systèmes : DRT/LIST/DILS
Abstract : We focus in this paper on generating models of quantified first-order formulas over built-in theories, which is paramount in software verification and bug finding. While standard methods are either geared toward proving the absence of solution or targeted to specific theories, we propose a generic approach based on a reduction to the quantifier-free case. Our technique allows thus to reuse all the efficient machinery developed for that context. Experiments show a substantial improvement over state-of-the-art methods.
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Submitted on : Wednesday, February 14, 2018 - 6:33:17 PM
Last modification on : Thursday, February 17, 2022 - 10:08:03 AM
Long-term archiving on: : Monday, May 7, 2018 - 4:16:59 AM


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  • HAL Id : cea-01709306, version 1
  • ARXIV : 1802.05616


Benjamin Farinier, Sébastien Bardin, Richard Bonichon, Marie-Laure Potet. Model Generation for Quantified Formulas: A Taint-Based Approach. 2018. ⟨cea-01709306⟩



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