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Counterexample-guided inductive synthesis for probabilistic systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU140799" target="_blank" >RIV/00216305:26230/21:PU140799 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/doi/10.1007/s00165-021-00547-2" target="_blank" >https://dl.acm.org/doi/10.1007/s00165-021-00547-2</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00165-021-00547-2" target="_blank" >10.1007/s00165-021-00547-2</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Counterexample-guided inductive synthesis for probabilistic systems

  • Original language description

    This paper presents counterexample-guided inductive synthesis (CEGIS) to automatically synthesise probabilistic models. The starting point is a family of finite-stateMarkov chains with related but distinct topologies. Such families can succinctly be described by a sketch of a probabilistic program. Program sketches are programs containing holes. Every hole has a finite repertoire of possible program snippets by which it can be filled.We study several synthesis problems-feasibility, optimal synthesis, and complete partitioning-for a given quantitative specification . Feasibility amounts to determine a family member satisfying , optimal synthesis amounts to find a family member that maximises the probability to satisfy , and complete partitioning splits the family in satisfying and refuting members. Each of these problems can be considered under the additional constraint of minimising the total cost of instantiations, e.g., what are all possible instantiations for  that are within a certain budget? The synthesis problems are tackled using a CEGIS approach. The crux is to aggressively prune the search space by using counterexamples provided by a probabilistic model checker. Counterexamples can be viewed as sub-Markov chains that rule out all family members that share this sub-chain. Our CEGIS approach leverages efficient probabilisticmodel checking,modern SMT solving, and programsnippets as counterexamples. Experiments on case studies froma diverse nature-controller synthesis, program sketching, and security-show that synthesis among up to a million candidate designs can be done using a few thousand verification queries.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GJ20-02328Y" target="_blank" >GJ20-02328Y: CAQtuS: Computer-Aided Quantitative Synthesis</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Formal Aspects of Computing

  • ISSN

    0934-5043

  • e-ISSN

    1433-299X

  • Volume of the periodical

    33

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    30

  • Pages from-to

    637-667

  • UT code for WoS article

    000648556100001

  • EID of the result in the Scopus database

    2-s2.0-85105498146