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PyQBF: A Python Framework for Solving Quantified Boolean Formulas

Research output: Contribution to journalArticlepeer-review

Abstract

Over the last years many solvers for quantified Boolean formulas (QBFs) have been developed. While most of these solvers support QDIMACS as a standard input format, exchanging a QBF solver within a reasoning framework is often a challenging task. Many solvers do not provide an API but they can only be used via their executable. Further, incremental solving is only supported to a limited extent.

We present PyQBF, a Python-based framework that provides a uniform programmatic interface to state-of-the-art QBF solvers. In this paper, we introduce the general architecture of PyQBF, describe the supported features and give a detailed example that illustrates how our framework can be used to implement an enumerative QBF solution counter as well as to solve a bounded model checking problem using a non-CNF representation. Our extensive experimental evaluation shows the efficiency of PyQBF. The experiments indicate that there is only little overhead compared to direct usage of the solvers.
Original languageEnglish
Number of pages12
JournalFormal Aspects of Computing
DOIs
Publication statusE-pub ahead of print - 16 Dec 2025

Fields of science

  • 101013 Mathematical logic
  • 102031 Theoretical computer science
  • 603109 Logic
  • 102011 Formal languages
  • 102022 Software development
  • 102001 Artificial intelligence
  • 102030 Semantic technologies
  • 102 Computer Sciences

JKU Focus areas

  • Digital Transformation

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