Attributes are an important concept for modeling data in practical applications. Up to now there is no adequate way to define attributes for different kinds of models used in -adhesive transformation systems, which are a special kind of graph transformation system based on -adhesive categories. Especially a proper representation and definition of attributes and their values as well as a suitable handling of the data does not fit well with other graph transformation formalisms. In this paper, we propose a new method to define attributes in a natural, but still formally precise and widely applicable way. We define a new kind of adhesive category, called -adhesive, that can be used for transformations of attributes, while the underlying models are still -adhesive ones. As a result, attributed models can be used as they are intended to be, but with a formal background and proven well-behavior. © 2012 Springer-Verlag.
CITATION STYLE
Golas, U. (2012). A general attribution concept for models in script M - Adhesive transformation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7562 LNCS, pp. 187–202). https://doi.org/10.1007/978-3-642-33654-6_13
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