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An Approach of Model Transformation Based on Attribute Grammars

  • May Dehayni
  • Louis Féraud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2817)

Abstract

Attribute grammars have been developed by Knuth [9] for the specification and implementation of static semantic aspects of programming languages. Since then, they have matured into a recognized field of study with many applications [17]. In this paper, we propose a system for transformation of information system models based on this formalism. First, the problem will be defined followed by the necessity for model transformation. Next, some model transformations approaches are presented, with special attention to XSLT. This brief survey gives the characteristics of the problem of model transformation and situates our approach. The semantics offered by attribute grammars brings the rigor of formal semantics while providing good performance at the implementation by a specific software called an evaluator. Thus, our system architecture consists essentially in defining a textual abstract syntax of the source meta-models and in building an attribute grammar to express the transformation. The input of the automatically generated evaluator is some text describing the source model, the syntax of which is defined by an abstract syntax. The output of the evaluator is another text corresponding to the target model in accordance with its grammar. In the last section, the characteristics and the benefits of our approach are discussed.

Keywords

Model Transformation Target Model Abstract Syntax Graph Grammar Semantic Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • May Dehayni
    • 1
  • Louis Féraud
    • 1
  1. 1.Institut de Recherche en Informatique de ToulouseUniversité Paul SabatierToulouse cedex 4France

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