By the same authors

EMG: A domain-specific transformation language for synthetic model generation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published copy (DOI)



Publication details

Title of host publicationTheory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings
DatePublished - 2016
Number of pages16
Original languageEnglish
ISBN (Print)9783319420639

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)03029743
ISSN (Electronic)16113349


Appropriate test models that can satisfy complex constraints are required for testing model management programs in order to build confidence in their correctness. Models have inherently complex structures and are often required to satisfy non-trivial constraints which makes them time consuming, labour intensive and error prone to construct manually. Automated capabilities are therefore required, however, existing fully-automated model generation tools cannot generate models that satisfy arbitrarily complex constraints. In this paper, we propose a semi-automated approach towards the generation of such models. A new framework named Epsilon Model Generator (EMG) that implements this approach is presented. The framework supports the development of model generators that can produce random and reproducible test models that satisfy complex constraints.

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