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FOCLASA 2018
16th International Workshop “Foundations of Coordination Languages and Self-adaptive Systems”
Toulouse, France, 26/06/2018
Nowadays software systems are distributed, concurrent, mobile, and often involve the composition of heterogeneous components and stand-alone services. Service coordination and self-adaptation constitute the core characteristics of distributed and service-oriented systems. Coordination languages and formal approaches to modelling and reasoning about self-adaptive behaviour help to simplify the development of complex distributed service-based systems, enable functional correctness proofs and improve reusability and maintainability of such systems. The goal of the FOCLASA workshop is to gather researchers and practitioners of the aforementioned fields, to share and identify common problems, and to devise general solutions in the context of coordination languages and self-adaptive systems.
temi di interesse
Theoretical models and frameworks for component and service coordination, service composition, service adaptation and concurrent system modeling
Applications and usability studies for the aforementioned theoretical models, interaction and coordination challenges in decentralized self-adaptive systems and various application domains
Languages and specification protocols for component and service interaction, their semantics, expressiveness, validation and verification, type checking, static and dynamic analysis
"Software as a Service" models (e.g., cloud computing) and dynamic software architectures, such as self-adaptive and self-organizing systems
Formal methods for self-adaptive systems, stochastic modeling and analysis, reasoning under uncertainty, run-time synthesis
Tools and environments for the development of concurrent and customizable self-monitoring, self-adaptive and self-organizing applications
Algorithms, mathematical models and realization frameworks for quality-of-service observation, storage, history-based analysis in self-adaptive systems (queuing models, load balancing, fault-tolerance analysis, machine learning systems)
Gul Agha • Pedro Alvarez • Farhad Arbab • Simon Bliudze • Radu Calinescu • Javier Cámara • Flavio De Paoli • Erik de Vink • Francisco J. Durán • Schahram Dustdar • Letterio Galletta • Eva Kühn • Alberto Lluch Lafuente • Sun Meng • Hernán C. Melgratti • Mohammad Mousavi • Pascal Poizat • José Proença • Gwen Salaün • Michael Sheng • Marjan Sirjani • Carolyn Talcott • Massimo Tivoli • Emilio Tuosto • Lina Ye • Gianluigi Zavattaro