We describe a formal methodology for the automatic synthesis of a secure orchestrator for a set of BPMN processes. The synthesized orchestrator is able to guarantee that all the processes that are started reach their end, and the resulting orchestrator process is secure, that is, it does not allow discloure of certain secret messages. In this work we present an implementation of a forth and back translation from BPMN to crypto-CCS, in such a way to exploit the PaMoChSA tool for synthesizing orchestrators. Furthermore, we study the problem of ranking orchestrators based on quantitative valuations of a process, and on the temporal evolution of such valuations and their security, as a function of the knowledge of the attacker.

Cloud computing promises easy access, low entry cost and elasticity. However, elastic service provisioning \nis usually delivered via service replication, which must be supervised manually, hand-picking the services \nto replicate and ensuring their proper load balance. Automated service provisioning, i.e., the function of \nautomatically scaling the services to cope up with their runtime demand, is a research challenge in cloud \ncomputing. In this work, we include such scalability analysis early in its development cycle, right at the design \nstage. We propose a model-driven approach where various QoS parameters can be simulated and analyzed \nusing the e-Motions tool. Additionally, the model is automatically transformed to fit the given throughput \nrequirements by replicating the services which cause the bottleneck. In order to evaluate the proposal, we \npresent some initial experimental results run over the e-Motions tool.

Adaptation is of utmost importance in systems developed by assembling reusable software services accessed through their public interfaces. This process aims at solving, as automatically as possible, mismatch cases which may be given at the different interoperability levels among interfaces by synthesizing a mediating adaptor. In this paper, we present a toolbox that fully supports the adaptation process, including: (i) different methods to construct adaptation contracts involving several services; (ii) simulation and verification techniques which help to identify and correct erroneous behaviours or deadlocking executions; and (iii) techniques for the generation of centralized or distributed adaptor protocols based on the aforementioned contracts. Our toolbox relates our models with implementation platforms, starting with the automatic extraction of behavioural models from existing interface descriptions, until the final adaptor implementation is generated for the target platform.