2017
DOI: 10.1007/978-3-319-61482-3_1
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On the Automated Derivation of Domain-Specific UML Profiles

Abstract: Similar to general-purpose languages, domain-specific languages (DSL) can be developed based on grammar formalisms, the model-driven engineering (MDE) is also becoming more and more important for the development of DSLs. On the one hand, metamodels can be used to define the syntax and semantics of DSLs. On the other hand, a DSL can be realized by adapting the Unified Modeling Language (UML) via the profiling mechanism, i.e., by defining a UML profile. For example, metamodels for a DSL can be created with the l… Show more

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Cited by 3 publications
(6 citation statements)
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“…We investigated the applicability of our approach to derive a UML profile and used the Test Description Language (TDL) [6] to evaluate the applicability of our derivation approach to new DSLs. In contrast, the Specification and Description Language (SDL) [21] was subject of another case study [27,28] to evaluate the applicability of our approach for existing DSLs with available production rules.…”
Section: Discussion Of the Evaluation Resultsmentioning
confidence: 99%
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“…We investigated the applicability of our approach to derive a UML profile and used the Test Description Language (TDL) [6] to evaluate the applicability of our derivation approach to new DSLs. In contrast, the Specification and Description Language (SDL) [21] was subject of another case study [27,28] to evaluate the applicability of our approach for existing DSLs with available production rules.…”
Section: Discussion Of the Evaluation Resultsmentioning
confidence: 99%
“…As mentioned before, we conducted another case study [27,29] where the Specification and Description Language (SDL) [21] served us to evaluate our derivation approach for grammar-based DSLs. The focus of our investigation was on the semi-automatic creation of an SDL metamodel based on production rules and on the automatic derivation of a UML profile and 'additional' metaclasses.…”
Section: Discussion Of the Evaluation Resultsmentioning
confidence: 99%
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