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A Formalized Classification Schema for Model Consistency

Kühn, Thomas; Fuchß, Dominik ORCID iD icon; Corallo, Sophie ORCID iD icon; König, Lars ORCID iD icon; Burger, Erik ORCID iD icon; Keim, Jan ORCID iD icon; Mazkatli, Manar ORCID iD icon; Sağlam, Timur ORCID iD icon; Reiche, Frederik ORCID iD icon; Koziolek, Anne ORCID iD icon; Reussner, Ralf

Abstract:

Although consistency is a widely used term, there is no common understanding in the modeling community on what consistency precisely means for model-based engineering. Nevertheless, most engineers would agree that models should be consistent to a certain degree to be useful. Although there are use case specific definitions of consistency and its properties, none of them are generally and independently applicable. As a result, we observed that engineers rarely employ a precise definition for their consistency notion. In addition, most engineers consider that models are consistent, neglecting that consistency usually relates model elements instead. To remedy these issues, we established a focus group of domain experts to derive a generally applicable and fine-grained notion of consistency. Using this fine-grained notion of consistency, we introduce a formalized classification schema for consistency covering seven dimensions. Afterwards this classification schema was applied by each domain expert to one of seven widely different model-based engineering scenarios. In turn, our schema provides a precise model-element-based definition of consistency and vocabulary for the modeling community to distinguish consistency relations. ... mehr


Volltext §
DOI: 10.5445/IR/1000161127
Veröffentlicht am 02.08.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Forschungsbericht/Preprint
Publikationsdatum 17.07.2023
Sprache Englisch
Identifikator ISSN: 2190-4782
KITopen-ID: 1000161127
Verlag Karlsruher Institut für Technologie (KIT)
Umfang 37 S.
Serie Karlsruhe Reports in Informatics ; 2023,1
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