Abstract
The paper is related to modeling and metamodeling disciplines, which are applicable in the software engineering domain. It is focused on the subject of finding the way leading to the selection of the right metamodel for a particular modeling problem. The approach introduced in the paper is based on a specific application of the Extended Graph Generalization, which is used to identify features of known metamodels in relation to the extensions and generalizations introduced by the Extended Graph Generalization definition. The discussion is related to an illustrative case-study. The paper introduces the Extended Graph Generalization definitions in Association-Oriented Metamodel, the Extended Graph Generalization symbolic notation, which are used when comparing features of different metamodels in relation to the Extended Graph Generalization features.
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Jodłowiec, M., Krótkiewicz, M., Zabawa, P. (2021). The Extended Graph Generalization as a Representation of the Metamodels’ Extensional Layer. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12798. Springer, Cham. https://doi.org/10.1007/978-3-030-79457-6_32
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DOI: https://doi.org/10.1007/978-3-030-79457-6_32
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