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In order to effectively validate the performance of software systems throughout their development cycle it is necessary to continuously build performance models from software models and then use the obtained models to check whether the system is being developed according to its performance requirements. The model building activity is a critical and effort-consuming activity. Several approaches have been envisaged to endow software designers with tools that automatically build ready-to-evaluate performance models from software development models. One essential requirement of such tools, often disregarded by current approaches, is a high degree of interoperability with software development tools, which has the positive effect of reducing both the level of required expertise in performance theory and the burden of learning separate tools. This paper introduces a framework for transforming source software models into target performance models. The transformation requires a clear understanding of the abstract syntax and semantics of both the source and target models, which is obtained by use of metamodeling techniques for defining the abstract syntax of models, the interrelationships between model elements and the model transformation rules. In the paper case, the framework is applied to the transformation of source models of UML type into target models of LQN (layered queueing network) type. The proposed approach is founded on the precepts recently introduced by model-driven development (MDA) and makes use of the set of related standards (MOF, QVT, XMI). This allows to obtain a high degree of automation, so that interoperable model transformation tools can be implemented in a timely and efficient way, leading to improvements in terms of software designers' productivity and system quality. *

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The analysis of modern business processes implemented as orchestration of software services demands for new approaches that explicitly take into account the inherent complexity and distribution characteristics of such processes. In this respect, Distributed Simulation (DS) offers a viable tool to cope with such a demand, due to the aggregation, scalability, representativeness and load balancing properties that it allows to achieve. However, the use of DS is mostly limited by the specialized technical know-how and the extra-development that DS requires with respect to approaches based on conventional local simulation. This paper proposes a model-driven method that enables the DS-based analysis of business processes by introducing the automated transformation of business process models into analysis models that are specified as Extended Queueing Network (EQN) models and executed as distributed simulations. The paper also presents an example application to a business process for an e-commerce scenario.

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