PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Ciancia V., Latella D., Massink M. On-the-fly mean-field model-checking for attribute-based coordination. In: COORDINATION 2016 - DisCoTec 2016 - Coordination Models and Languages. 18th IFIP WG 6.1 International Conference - Held as Part of the 11th International Federated Conference on Distributed Computing Techniques (Heraklion, Crete, Greece, 6-9 June 2016). Proceedings, pp. 67 - 83. A. Lluch Lafuente, J. Proença (eds.). (Lecture Notes in Computer Science, vol. 9686). Springer, 2016.
 
 
Abstract
(English)
Typical Collective Adaptive Systems (CAS) consist of a large number of interacting objects that coordinate their activities in a decentralised and often implicit way. The design of such systems is challenging, as it requires scalable analysis tools and methods to check properties of proposed system designs before they are put into operation. A promising technique is Fast Mean-Field Approximated Model-checking. The FlyFast model-checker uses an on-the-fly algorithm for bounded PCTL model-checking of selected individuals in the context of very large populations whose global behaviour is approximated using deterministic limit techniques. Recently, specific modelling languages have been proposed for CAS. A key feature of such languages is the attribute-based interaction paradigm. In this paper we present an attribute-based coordination language as a front-end for FlyFast. Its formal probabilistic semantics is provided and a translation to the original FlyFast language is given and proved correct. Application examples are also provided.
URL: http://link.springer.com/chapter/10.1007/978-3-319-39519-7_5
DOI: 10.1007/978-3-319-39519-7_5
Subject Collective Adaptive Systems
Coordination Languages
Probabilistic model-checking
On-the-fly model-checking
Mean-field approximation
Discrete time Markov chains
B.8.2 Performance Analysis and Design Aids
D.2.4 Software/Program Verification
F.1.2 Modes of Computation
F.3.1 Specifying and Verifying and Reasoning about Programs
G.3 PROBABILITY AND STATISTICS
39-XX Difference and functional equations
60Jxx Markov processes


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