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.
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 language | English |
|---|---|
| Number of pages | 12 |
| Journal | Formal Aspects of Computing |
| DOIs | |
| Publication status | E-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
Research output
- 1 Conference proceedings
-
PyQBF: A Python Framework for Solving Quantified Boolean Formulas
Peyrer, M., Heisinger, M. & Seidl, M., Nov 2024, Integrated Formal Methods, 19th International Conference (IFM 2024). Cham: Springer, Vol. 15234. p. 279–287 9 p. (Lecture Notes in Computer Science).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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