CTL Model Checking in the Cloud Using MapReduce

The recent extensive availability of "big data" platforms calls for a widespread adoption by the formal verification community. Cloud computing platforms represent a great opportunity to run massively parallel jobs, yet classical formal verification tools/techniques must undergo a deep tec...

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Bibliographic Details
Published in:2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing pp. 333 - 340
Main Authors: Camilli, Matteo, Bellettini, Carlo, Capra, Lorenzo, Monga, Mattia
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2014
Subjects:
Big data
Cloud computing
Complexity theory
Computational modeling
Context modeling
CTL
Distributed algorithms
Formal Verification
MapReduce
Model checking
ISBN:9781479984473, 1479984477
Online Access:Get full text
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Summary:The recent extensive availability of "big data" platforms calls for a widespread adoption by the formal verification community. Cloud computing platforms represent a great opportunity to run massively parallel jobs, yet classical formal verification tools/techniques must undergo a deep technological transformation in order to exploit the new available architectures. This has raised an increasing interest in deploying verification techniques on parallel/distributed frameworks. In this paper we introduce a framework to ease the adoption of a distributed approach to verification of Computation Tree Logic (CTL) formulas on very large state spaces. The approach exploits/integrates a recently developed, parametric state-space builder. The whole framework adopts M AP R EDUCE as core computational model, and can be tailored to different modelling formalisms. The outcomes of several tests performed on (Petri-nets based) benchmark specifications are presented, thus showing the convenience of the proposed approach.
ISBN:9781479984473
1479984477
DOI:10.1109/SYNASC.2014.52