Model-driven Generative Development of Measurement SoftwareReport as inadecuate

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1 Department of Computer Science 2 TRISKELL - Reliable and efficient component based software engineering IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique 3 LISYC - Laboratoire d-Informatique des Systèmes Complexes 4 E3I2 - Extraction et Exploitation de l-Information en Environnements Incertains

Abstract : Metrics offer a practical approach to evaluate non-functional properties of domain-specific models. However, it is tedious and costly to develop and maintain a measurement software for each domain specific modeling language DSML. In this paper, we present the principles of a domain-independent, metamodel-independent and generative approach to measuring models. The approach is operationalized through a prototype that synthesizes a measurement infrastructure for a DSML. This model-driven measurement approach is model-driven from two viewpoints: 1 it measures models of a domain specific modeling language; 2 it uses models as unique and consistent metric specifications, w.r.t. a metric specification metamodel. The metric metamodel captures all the necessary concepts for model-based specifications of metrics. The specifications are used to generate a fully fledged implementation of a measurement tool. The benefit from applying the approach is evaluated by three applicative case studies. They indicate that this approach significantly reduces the domain-specific measurement software development cost with respect to code volume.

Author: Martin Monperrus - Jean-Marc Jézéquel - Benoit Baudry - Joël Champeau - Brigitte Hoeltzener -



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