A model transformation framework for the automated building of performance models from UML models

ABSTRACT

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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INDEX TERMS

Keywords:
LQN, MDA, UML, automated model building, model transformation, software performance