“Pono: A Flexible and Extensible SMT-based Model Checker” by Makai Mann, Ahmed Irfan, Florian Lonsing, Yahan Yang, Hongce Zhang, Kristopher Brown, Aarti Gupta, and Clark Barrett. In Proceedings of the 33^rd International Conference on Computer Aided Verification (CAV '21), (Rustan Leino and Alexandra Silva, eds.), July 2021, pp. 461-474.
Symbolic model checking is an important tool for finding bugs (or proving the absence of bugs) in modern system designs. Because of this, improving the ease of use, scalability, and performance of model checking tools and algorithms continues to be an important research direction. In service of this goal, we present Pono, an open-source SMT-based model checker. Pono is designed to be both a research platform for developing and improving model checking algorithms, as well as a performance-competitive tool that can be used for academic and industry verification applications. In addition to performance, Pono prioritizes transparency (developed as an open-source project on GitHub), flexibility (Pono can be adapted to a variety of tasks by exploiting its general SMT-based interface), and extensibility (it is easy to add new algorithms and new back-end solvers). In this paper, we describe the design of the tool with a focus on the flexible and extensible architecture, cover its current capabilities, and demonstrate that Pono is competitive with state-of-the-art tools.
BibTeX entry:
@inproceedings{MIL+21,
author = {Makai Mann and Ahmed Irfan and Florian Lonsing and Yahan Yang
and Hongce Zhang and Kristopher Brown and Aarti Gupta and Clark
Barrett},
editor = {Rustan Leino and Alexandra Silva},
title = {Pono: A Flexible and Extensible {SMT}-based Model Checker},
booktitle = {Proceedings of the {\it 33^{rd}} International Conference
on Computer Aided Verification (CAV '21)},
series = {Lecture Notes in Computer Science},
volume = {12760},
pages = {461--474},
publisher = {Springer International Publishing},
month = jul,
year = {2021},
doi = {10.1007/978-3-030-81688-9_22},
url = {http://theory.stanford.edu/~barrett/pubs/MIL+21.pdf}
}
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