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Efficient Solver Scheduling and Selection for Satisfiability Modulo Theories (SMT) Problems.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F24%3AA2502N61" target="_blank" >RIV/61988987:17610/24:A2502N61 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scitepress.org/Papers/2024/123936/123936.pdf" target="_blank" >https://www.scitepress.org/Papers/2024/123936/123936.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0012393600003654" target="_blank" >10.5220/0012393600003654</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Efficient Solver Scheduling and Selection for Satisfiability Modulo Theories (SMT) Problems.

  • Original language description

    This paper introduces innovative concepts for improving the process of selecting solvers from a portfolio to tackle Satisfiability Modulo Theories (SMT) problems. We propose a novel solver scheduling approach that significantly enhances solving performance, measured by the PAR-2 metric, on selected benchmarks. Our investigation reveals that, in certain cases, scheduling based on a crude statistical analysis of training data can perform just as well, if not better, than a machine learning predictor. Additionally, we present a dynamic scheduling approach that adapts in real-time, taking into account the changing likelihood of solver success. These findings shed light on the nuanced nature of solver selection and scheduling, providing insights into situations where data-driven methods may not offer clear advantages.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2024)

  • ISBN

    978-989-758-684-2

  • ISSN

    2184-4313

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    360-369

  • Publisher name

    SCITEPRESS

  • Place of publication

    Řím

  • Event location

    Itálie

  • Event date

    Feb 24, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article