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SAT 2022

Pedant: A Certifying DQBF Solver

Conference Paper Accepted Paper Logic in Computer Science ยท Satisfiability

Abstract

Pedant is a solver for Dependency Quantified Boolean Formulas (DQBF) that combines propositional definition extraction with Counterexample-Guided Inductive Synthesis (CEGIS) to compute a model of a given formula. Pedant 2 improves upon an earlier version in several ways. We extend the notion of dependencies by allowing existential variables to depend on other existential variables. This leads to more and smaller definitions, as well as more concise repairs for counterexamples. Additionally, we reduce counterexamples by determining minimal separators in a conflict graph, and use decision tree learning to obtain default functions for undetermined variables. An experimental evaluation on standard benchmarks showed a significant increase in the number of solved instances compared to the previous version of our solver.

Authors

Keywords

  • DQBF
  • DQBF Solver
  • Decision Procedure
  • Certificates

Context

Venue
International Conference on Theory and Applications of Satisfiability Testing
Archive span
2003-2025
Indexed papers
824
Paper id
835233433997994086
v2026.09.13