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Beyond stereotyping: metamodeling approaches for the UML

Authors: Ansgar Schleicher; Bernhard Westfechtel;

Beyond stereotyping: metamodeling approaches for the UML

Abstract

UML is being used as the universal technique for modeling object-oriented applications across a wide range of domains. Developing a truly adequate uniform modeling technique in the face of these diverse domains seems an unsolvable quest and contrasts domain specific software engineering activities. Recently, many adaptations to UML have been made to reflect a domain's world view. These adaptations often exceed the UML's own extension mechanisms and result in yet another urban UML slang. However, domain-specifically adapting the UML metamodel becomes increasingly important in the context of model checking and code generation mechanisms. Therefore solutions should be found to fully support metamodeling within the UML and UML CASE tools. The paper discusses and evaluates the UML's inherent as well as proprietary metamodeling approaches and provides domain driven ideas for a meta-modeling approach for a diversely used Unified Modeling Language.

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    popularity
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    Average
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Top 10%
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