Towards Model Transformation Generation By-Example

Abstract

With the advent of Model-Driven Engineering (MDE) several model transformation approaches and languages have been developed in the previous 5 years. Most of these existing approaches are metamodel-based with metamodels representing both an abstract syntax of the corresponding modeling language and also a data structure for storing models. However, this implementation specific focus makes it difficult for modelers to develop model transformations, because metamodels do not necessarily define all language concepts explicitly which are available for notation purposes. Therefore, we propose a by-example approach for defining inter-model mappings representing semantic correspondences between concrete domain models, which is more user-friendly, then directly specifying model transformation rules or mappings based on the abstract syntax. The intermodel mappings between domain models can be used to generate model transformation rules, by-example, taking into account the already defined mapping between abstract and concrete syntax elements. With this approach the user's knowledge about the notation of the modeling language is sufficient for the definition of model transformations regarding semantic correspondences. Hence, no detailed knowledge about the metamodel and the model transformation language is required.

From UML to Alloy and back again

“…In [25,22], discussion is on infering model transformation rules using a manually created mapping between particular models i.e. model transformation rules from an example.…”

Horizontal Transformations of Visual Models in MetaLanguage System

“…All it does impossible the usage of this approach in the MetaLanguage system. MTBE approach [17] is quite non-standard and unusual. The main purpose of MTBE is automatic generation of transformation rules on a basis of an initial set of learning examples.…”

Content Based Model Transformations: Solutions to Existing Issues with Application in Information Security

“…Therefore new solutions are proposed to improve the process and provide an alternative method that improves the efficiency and accuracy of the transformations. In this chapter ideas on how current situation in specific situations can be improved using advanced techniques, such as grammar-based model transformations [21] and model transformation by-example [22][23][24][25] element identification are presented.…”