By the same authors

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

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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
Pages36-51
Number of pages16
PublisherSpringer-Verlag
Volume9765
Original languageEnglish
ISBN (Print)9783319420639

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9765
ISSN (Print)03029743
ISSN (Electronic)16113349

Abstract

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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