Issue No. 06 - November/December (2009 vol. 35)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TSE.2009.31
Colin Atkinson , University of Mannheim, Mannheim
Matthias Gutheil , itemis AG, Bonn
Bastian Kennel , University of Mannheim, Mannheim
Although domain-specific modeling tools have come a long way since the modern era of model-driven development started in the early 1990s and now offer an impressive range of features, there is still significant room for enhancing the flexibility they offer to end users and for combining the advantages of domain-specific and general-purpose languages. To do this, however, it is necessary to enhance the way in which the current generation of tools view metamodeling and support the representation of the multiple, “ontological” classification levels that often exist in subject domains. State-of-the-art tools essentially allow users to describe the abstract and concrete syntaxes of a language in the form of metamodels and to make statements in that language in the form of models. These statements typically convey information in terms of types and instances in the domain (e.g., the classes and objects of UML), but not in terms of types of types (i.e., domain metaclasses), and types of types of types, and so on, across multiple classification levels. In essence, therefore, while they provide rich support for “linguistic” metamodeling, the current generation of tools provides little if any built-in support for modeling “ontological” classification across more than one type/instance level in the subject domain. In this paper, we describe a prototype implementation of a new kind of modeling infrastructure that, by providing built-in support for multiple ontological as well as linguistic classification levels, offers various advantages over existing language engineering approaches and tools. These include the ability to view a single model from the perspective of both a general-purpose and a domain-specific modeling language, the ability to define constraints across multiple ontological classification levels, and the ability to tie the rendering of model elements to ontological as well as linguistic types over multiple classification levels. After first outlining the key conceptual ingredients of this new infrastructure and presenting the main elements of our current realization, we show these benefits through two small examples.
Language engineering, metamodeling, multilevel modeling.
C. Atkinson, B. Kennel and M. Gutheil, "A Flexible Infrastructure for Multilevel Language Engineering," in IEEE Transactions on Software Engineering, vol. 35, no. , pp. 742-755, 2009.