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Generating Instance Models from Meta Models

  • Karsten Ehrig
  • Jochen M. Küster
  • Gabriele Taentzer
  • Jessica Winkelmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4037)

Abstract

Meta modeling is a wide-spread technique to define visual languages, with the UML being the most prominent one. Despite several advantages of meta modeling such as ease of use, the meta modeling approach has one disadvantage: It is not constructive i. e. it does not offer a direct means of generating instances of the language. This disadvantage poses a severe limitation for certain applications. For example, when developing model transformations, it is desirable to have enough valid instance models available for large-scale testing. Producing such a large set by hand is tedious. In the related problem of compiler testing, a string grammar together with a simple generation algorithm is typically used to produce words of the language automatically. In this paper, we introduce instance-generating graph grammars for creating instances of meta models, thereby overcoming the main deficit of the meta modeling approach for defining languages.

Keywords

Class Diagram Object Constraint Language Graph Transformation Meta Model Type Graph 
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

© IFIP International Federation for Information Processing 2006

Authors and Affiliations

  • Karsten Ehrig
    • 1
  • Jochen M. Küster
    • 2
  • Gabriele Taentzer
    • 3
  • Jessica Winkelmann
    • 3
  1. 1.Department of Computer ScienceUniversity of LeicesterUK
  2. 2.IBM Zurich Research LaboratoryRüschlikonSwitzerland
  3. 3.Department of Computer ScienceTechnical University of BerlinGermany

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