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tacas-artifact-coupledsim.zip (720.26 MB)
Isabelle/HOL proof and Apache Flink program for TACAS 2019 paper: Computing Coupled Similarity
software
posted on 2019-03-12, 18:44 authored by Benjamin BispingOur TACAS 2019 publication presents a game-theoretic algorithm to compute coupled similarity, running in cubic time and space with respect to the number of states in the input transition system. We show that one cannot hope for much better because deciding the coupled simulation preorder is at least as hard as deciding the weak simulation preorder.
This artifact backs claims from the paper:
* The theoretical key results concerning game characterization, reducibility, and polynomial algorithm solution are supported by machine-checkable proofs using Isabelle/HOL
* We provide the source code of an experimental Scala implementation of the game algorithm using the Apache Flink framework for scalable parallelized computations.
* The artifact also contains scripts to run the Flink implementation against some samples from the Very Large Transition Sytems Benchmark Suite and to measure running time and model sizes. This also shows that weak bisimilarity and coupled similarity coincide for these systems.
* We moreover include the dependencies (Isabelle2018, Scala, SBT, and Apache Flink) needed to run the artifacts within the TACAS VM (https://springernature.figshare.com/articles/TACAS_2019_Artifact_Evaluation_VM/7823978) Please note that the packaged dependencies are subject to their respective licences.
About Coupled Similarity:
Coupled similarity is a notion of equivalence for systems with internal
actions. It has outstanding applications in contexts where internal
choices must transparently be distributed in time or space, for example,
in process calculi encodings or in action refinements. No tractable
algorithms for the computation of coupled similarity have been proposed up to now. Accordingly, there has not been any tool support.