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.
| Originalsprache | Englisch |
|---|---|
| Seitenumfang | 12 |
| Fachzeitschrift | Formal Aspects of Computing |
| DOIs | |
| Publikationsstatus | Elektronische Veröffentlichung vor Drucklegung - 16 Dez. 2025 |
Wissenschaftszweige
- 101013 Mathematische Logik
- 102031 Theoretische Informatik
- 603109 Logik
- 102011 Formale Sprachen
- 102022 Softwareentwicklung
- 102001 Artificial Intelligence
- 102030 Semantische Technologien
- 102 Informatik
JKU-Schwerpunkte
- Digital Transformation
Publikationen
- 1 Konferenzbeitrag
-
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, Band 15234. S. 279–287 9 S. (Lecture Notes in Computer Science).Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung
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