Model-Driven Engineering tools require model instances for testing, validation, and demonstration purposes, yet manually creating such instances is tedious and error-prone. This paper presents the EMF Model Generator, a lightweight Java library for programmatically generating valid model instances from Eclipse Modeling Framework (EMF) metamodels. The tool uses a deterministic, configurable approach based on specialized setter components for attributes, containment references, cross-references, and feature maps, producing reproducible results. It handles complex EMF semantics including bidirectional references, multiplicity constraints, abstract classes with polymorphic instantiation, recursive containment structures, and heterogeneous feature maps. The architecture provides multiple customization levels, from high-level configuration to per-feature functions and complete setter replacement. The tool integrates directly with EMF’s reflective API without external dependencies, making it suitable for testing, prototyping, and demonstration purposes where predictable, valid model instances are needed.
EMF Model Generator: A Configurable Library for Generating Valid and Reproducible Model Instances / Bettini Lorenzo. - STAMPA. - 1:(2026), pp. 520-527. ( 14th International Conference on Model-Based Software and Systems Engineering, MODELSWARD 2026 esp 2026) [10.5220/0014619100004058].
EMF Model Generator: A Configurable Library for Generating Valid and Reproducible Model Instances
Bettini Lorenzo
2026
Abstract
Model-Driven Engineering tools require model instances for testing, validation, and demonstration purposes, yet manually creating such instances is tedious and error-prone. This paper presents the EMF Model Generator, a lightweight Java library for programmatically generating valid model instances from Eclipse Modeling Framework (EMF) metamodels. The tool uses a deterministic, configurable approach based on specialized setter components for attributes, containment references, cross-references, and feature maps, producing reproducible results. It handles complex EMF semantics including bidirectional references, multiplicity constraints, abstract classes with polymorphic instantiation, recursive containment structures, and heterogeneous feature maps. The architecture provides multiple customization levels, from high-level configuration to per-feature functions and complete setter replacement. The tool integrates directly with EMF’s reflective API without external dependencies, making it suitable for testing, prototyping, and demonstration purposes where predictable, valid model instances are needed.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



