Abstract
Coordination languages are intended to simplify the development of complex software systems by separating the coordination aspects of an application from its computational aspects. Coordination refers to the ways the independent active pieces of a program (e.g. a process, a task, a thread, etc.) communicate and synchronise with each other. We review various approaches to introducing probabilistic or stochastic features in coordination languages. The main objective of such a study is to develop a semantic basis for a quantitative analysis of systems of interconnected or interacting components, which allows us to address not only the functional (qualitative) aspects of a system behaviour but also its non-functional aspects, typically considered in the realm of performance modelling and evaluation.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
- Parallel Operator
- Operational Semantic
- Parallel Composition
- Abstract Interpretation
- Discrete Time Markov Chain
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Gelernter, D.: Generative communication in linda. ACM Trans. Program. Lang. Syst. 7, 80–112 (1985)
Gelernter, D., Carriero, N.: Coordination languages and their significance. Commun. ACM 35, 97–107 (1992)
Arbab, F.: Manifold. Future Generation Computer Systems 10, 273–277 (1994)
Sands, D., Weichert, M.: From gamma to cbs: Refining multiset transformations with broadcasting processes. In: El-Rewini, H. (ed.) Proceedings of 31st Hawaii International Conference on System Sciences, vol. VII, pp. 265–274. IEEE, Los Alamitos (1998)
Bravetti, M., Gorrieri, R., Lucchi, R., Zavattaro, G.: Quantitative information in the tuple space coordination model. Theoretical Computer Science (to appear)
Di Pierro, A., Hankin, C., Wiklicky, H.: Probabilistic KLAIM. In: Nicola, R.D., Ferrari, G., Meredith, G. (eds.) COORDINATION 2004. LNCS, vol. 2949, pp. 119–134. Springer, Heidelberg (2004)
Di Pierro, A., Hankin, C., Wiklicky, H.: Continuous-time probabilistic KLAIM. In: SecCo 2004 — CONCUR Workshop on Security Issues in Coordination Models, Languages, and Systems. Electronic Notes in Theoretical Computer Science. Elsevier, Amsterdam (2004)
Nicola, R.D., Latella, D., Massink, M.: Formal modeling and quantitative analysis of KLAIM-based mobile systems. In: 20th Annual ACM Symposium on Applied Computing. ACM, New York (2005)
van Glabbeek, R., Smolka, S., Steffen, B.: Reactive, generative and stratified models of probabilistic processes. Information and Computation 121, 59–80 (1995)
De Nicola, R., Ferrari, G., Pugliese, R.: KLAIM: A kernel language for agents interaction and mobility. IEEE Transactions on Software Engineering 24, 315–330 (1998)
Hillston, J.: PEPA: Performance enhanced process algebra. Technical Report CSR-24-93, University of Edinburgh, Edinburgh, Scotland (1993)
Tijms, H.C.: Stochastic Models – An Algorithmic Approach. John Wiley & Sons, Chichester (1994)
Norris, J.R.: Markov Chains. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge (1997)
Bause, F., Kritzinger, P.S.: Stochastic Petri Nets – An Introduction to the Theory, 2nd edn. Vieweg Verlag (2002)
Cousot, P., Cousot, R.: Abstract Interpretation and Applications to Logic Programs. Journal of Logic Programming 13, 103–180 (1992)
Nielson, F., Nielson, H.R., Hankin, C.: Principles of Program Analysis. Springer, Heidelberg (1999)
Di Pierro, A., Wiklicky, H.: Concurrent Constraint Programming: Towards Probabilistic Abstract Interpretation. In: Proceedings of PPDP 2000, Montréal, Canada, pp. 127–138. ACM, New York (2000)
Di Pierro, A., Wiklicky, H.: Linear structures for concurrency in probabilistic programming languages. In: Proceedings of MFCSIT 2000 – First Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, Cork, Ireland. Electronic Notes in Theoretical Computer Science, vol. 40. Elsevier, Amsterdam (2001)
Di Pierro, A., Wiklicky, H.: Operator algebras and the operational semantics of probabilistic languages. In: Proceedings of MFCSIT 2004 – Third Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, Dublin, Ireland. Electronic Notes in Theoretical Computer Science. Elsevier, Amsterdam (2004) (to appear)
Böttcher, A., Silbermann, B.: Introduction to Large Truncated Toeplitz Matrices. Springer, New York (1999)
Deutsch, F.: Best Approximation in Inner Product Spaces. CMS Books in Mathematics, vol. 7. Springer, New York (2001)
Di Pierro, A., Hankin, C., Wiklicky, H.: Measuring the confinement of probabilistic systems. Theoretical Computer Science 340, 3–56 (2005)
Ben-Israel, A., Greville, T.: Generalised Inverses — Theory and Applications, 2nd edn. CMS Books in Mathematics, vol. 15. Springer, New York (2003)
Di Pierro, A., Hankin, C., Wiklicky, H.: Quantitative relations and approximate process equivalences. In: Amadio, R.M., Lugiez, D. (eds.) CONCUR 2003. LNCS, vol. 2761, pp. 508–522. Springer, Heidelberg (2003)
Di Pierro, A., Hankin, C., Wiklicky, H.: Quantitative static analysis of distributed systems. Journal of Functional Programming 15, 1–47 (2005)
Friedberg, S., Insel, A., Spence, L.: Linear Algebra, 4th edn. Prentice Hall, Englewood Cliffs (2003)
Prasolov, V.: Problems and Theorems in Linear Algebra. Translation of Mathematical Monographs, vol. 134. American Mathematical Society, Providence (1994)
Hirsch, M., Smale, S.: Differential Equations, Dynamical Systems, and Linear Algebra. Academic Press, Orlando (1974)
Giacalone, A., Jou, C.C., Smolka, S.: Algebraic reasoning for probabilistic concurrent systems. In: Proceedings of the IFIP WG 2.2/2.3 Working Conference on Programming Concepts and Methods, Sea of Galilee, April 1990, pp. 443–458. North-Holland, Amsterdam (1990)
Jonsson, B., Yi, W., Larsen, K.: 11. In: Probabilistic Extensions of Process Algebras, pp. 685–710. Elsevier Science, Amsterdam (2001), see [?]
Di Pierro, A., Wiklicky, H.: Quantitative Observables and Averages in Probabilistic Constraint Programming. In: Apt, K., Kakas, T., Monfroy, E., Rossi, F. (eds.) Compulog Net WS 1999. LNCS (LNAI), vol. 1865, p. 212. Springer, Heidelberg (2000)
Priami, C.: Stochastic π-calculus. Computer Journal 38, 578–589 (1995)
Hillston, J.: A Compositional Approach to Performance Modelling. Cambridge University Press, Cambridge (1996)
Bernardo, M., Gorrieri, R.: A tutorial on empa: A theory of concurrent processes with nondeterminism, priorities, probabilities and time. Technical Report UBLCS-96-17, Department of Computer Science, University of Bologna (1997)
Kwiatkowska, M., Norman, G., Parker, D.: Probabilistic symbolic model checking with PRISM: A hybrid approach. In: Katoen, J.P., Stevens, P. (eds.) TACAS 2002. LNCS, vol. 2280, pp. 52–66. Springer, Heidelberg (2002)
de Alfaro, L.: Formal Verification of Probabilistic Systems. PhD thesis, Stanford University, Department of Computer Science (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Di Pierro, A., Hankin, C., Wiklicky, H. (2005). Probabilistic Linda-Based Coordination Languages. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, WP. (eds) Formal Methods for Components and Objects. FMCO 2004. Lecture Notes in Computer Science, vol 3657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11561163_6
Download citation
DOI: https://doi.org/10.1007/11561163_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29131-2
Online ISBN: 978-3-540-31939-9
eBook Packages: Computer ScienceComputer Science (R0)