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ATL only uses regular expressions for replacing and splitting strings. Future research may include development of a custom string ATL library that will provide helpers that implement regular expression matching operations. Furthermore, we have assumed that messages in the primary and aspect models have simple arguments that are either strings or integers. However, messages can have arguments that are instances of classes defined in the structural view of the system. Therefore, the current use of lazy rules to create message arguments (and class operation parameters) may not be ideal.

Sabetta, "Performance Analysis of Aspect- Oriented UML Models", Software and Systems Modeling (SoSyM), Vol. 6, No. , pages. 453-471, 2007, Springer Berlin / Heidelberg D. Pilone, and N. 0 in a Nutshell”, O'Reilly, (June 2005 ) ISBN: 0-596-007957 G. Straw, G. Georg, E. Song, S. Ghosh, R. France, and J. M. Bieman, “Model Composition Directives,” LNCS 3273, pages 84-97, 2004, Springer Berlin / Heidelberg J. Whittle, J. Araújo, and A. Moreira, “Composing aspect models with graph transformations,” In Proceedings of the 2006 international workshop on Early aspects at ICSE, pages 59-65, Shanghai, China, 2006 J.

It is easy and intuitive to use. It allows for easy model migration. uml or XMI files. It allows for model validation (not available in some of the tools) which we found very useful. RSA can also generate a sequence diagram from an imported model. This makes verification of our composed model easy and less error prone. The use of a mark model. ATL Transformations only work with models; therefore, our binding rules have to be in the form of a model that has a metamodel. Mark models are a convenient way to work with parameterized transformations.

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