Abstract
The LTSmin toolset provides multiple generation and on-the-fly analysis algorithms for large graphs (state spaces), typically generated from concise behavioral specifications (models) of systems. LTSmin supports a variety of input languages, but its key feature is modularity: language frontends, optimization layers, and algorithmic backends are completely decoupled, without sacrificing performance. To complement our existing symbolic and distributed model checking algorithms, we added a multi-core backend for checking safety properties, with several new features to improve efficiency and memory usage: low-overhead load balancing, incremental hashing and scalable state compression. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Laarman, A., Van De Pol, J., & Weber, M. (2011). Multi-core LTSmin: Marrying modularity and scalability. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6617 LNCS, pp. 506–511). https://doi.org/10.1007/978-3-642-20398-5_40
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