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Constraint Modularization Within Multi-level Meta-modeling

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 756))

Abstract

Traditional meta-modeling strictly differentiates between internal and external constraints attached to the meta-models. While for example cardinality and annotations are usually considered existential parts of the meta-modeling techniques, OCL expressions are treated as an independent layer of constraint mechanism. The result is a patchwork because the external constraint notation will not become part of the meta-model, its semantics is only referentially integrated, and thus meta-levels are to be harmonized. In comparison, multi-level meta-modeling may enable a uniform self-contained interpretation of the constraint semantics by encapsulating the constraint modeling constructs into the fabric of the multi-level meta-modeling framework. In this paper, we describe such a modular constraint modeling technique that has been formalized in Dynamic Multi-Layer Algebra (DMLA), an algebraic multi-level meta-modeling method. The paper first describes our constraint modeling approach and then elaborates on the concept of cardinality and its trivial generalization to regular expression patterns. As motivated by one of the interface modeling languages of network management, the approach is also demonstrated on a simple YANG language construct.

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References

  1. YANG – A Data Modeling Language for the Network Configuration Protocol (NETCONF). https://tools.ietf.org/html/rfc6020

  2. Emfatic. https://www.eclipse.org/emfatic/

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Correspondence to Zoltán Theisz .

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Theisz, Z., Urbán, D., Mezei, G. (2017). Constraint Modularization Within Multi-level Meta-modeling. In: Damaševičius, R., Mikašytė, V. (eds) Information and Software Technologies. ICIST 2017. Communications in Computer and Information Science, vol 756. Springer, Cham. https://doi.org/10.1007/978-3-319-67642-5_24

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  • DOI: https://doi.org/10.1007/978-3-319-67642-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67641-8

  • Online ISBN: 978-3-319-67642-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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