A Generic Set Theory-Based Pattern Matching Approach for the Analysis of Conceptual Models
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Abstract
Recognizing patterns in conceptual models is useful for a number of purposes, like revealing syntactical errors, model comparison, and identification of business process improvement potentials. In this contribution, we introduce an approach for the specification and matching of structural patterns in conceptual models. Unlike existing approaches, we do not focus on a certain application problem or a specific modeling language. Instead, our approach is generic making it applicable for any pattern matching purpose and any conceptual modeling language. In order to build sets representing structural model patterns, we define operations based on set theory, which can be applied to arbitrary sets of model elements and relationships. Besides a conceptual specification of our approach, we present a prototypical modeling tool that shows its applicability.
Keywords
Conceptual Modeling Pattern Matching Set TheoryPreview
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