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

Saheed Popoola; Dimitrios S. Kolovos; Horacio Hoyos Rodriguez

doi:10.1007/978-3-319-42064-6_3

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

Saheed Popoola^*, Dimitrios S. Kolovos, Horacio Hoyos Rodriguez

^*Corresponding author for this work

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings
Publisher	Springer
Pages	36-51
Number of pages	16
Volume	9765
ISBN (Print)	9783319420639
DOIs	https://doi.org/10.1007/978-3-319-42064-6_3
Publication status	Published - 2016
Event	9th International Conference on Theory and Practice of Model Transformations, ICMT 2016 Held as Part of Conference on Software Technologies: Applications and Foundations, STAF 2016 - Vienna, Austria Duration: 4 Jul 2016 → 5 Jul 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9765
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	9th International Conference on Theory and Practice of Model Transformations, ICMT 2016 Held as Part of Conference on Software Technologies: Applications and Foundations, STAF 2016
Country/Territory	Austria
City	Vienna
Period	4/07/16 → 5/07/16

Access to Document

10.1007/978-3-319-42064-6_3

Cite this

Popoola, S., Kolovos, D. S., & Rodriguez, H. H. (2016). EMG: A domain-specific transformation language for synthetic model generation. In Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings (Vol. 9765, pp. 36-51). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9765). Springer. https://doi.org/10.1007/978-3-319-42064-6_3

Popoola, Saheed ; Kolovos, Dimitrios S. ; Rodriguez, Horacio Hoyos. / EMG : A domain-specific transformation language for synthetic model generation. Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings. Vol. 9765 Springer, 2016. pp. 36-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

author = "Saheed Popoola and Kolovos, {Dimitrios S.} and Rodriguez, {Horacio Hoyos}",

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Popoola, S, Kolovos, DS & Rodriguez, HH 2016, EMG: A domain-specific transformation language for synthetic model generation. in Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings. vol. 9765, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9765, Springer, pp. 36-51, 9th International Conference on Theory and Practice of Model Transformations, ICMT 2016 Held as Part of Conference on Software Technologies: Applications and Foundations, STAF 2016, Vienna, Austria, 4/07/16. https://doi.org/10.1007/978-3-319-42064-6_3

EMG: A domain-specific transformation language for synthetic model generation. / Popoola, Saheed; Kolovos, Dimitrios S.; Rodriguez, Horacio Hoyos.
Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings. Vol. 9765 Springer, 2016. p. 36-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9765).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T2 - 9th International Conference on Theory and Practice of Model Transformations, ICMT 2016 Held as Part of Conference on Software Technologies: Applications and Foundations, STAF 2016

AU - Popoola, Saheed

AU - Kolovos, Dimitrios S.

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PY - 2016

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AB - 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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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Popoola S, Kolovos DS , Rodriguez HH. EMG: A domain-specific transformation language for synthetic model generation. In Theory and Practice of Model Transformations - 9th International Conference, ICMT 2016 Held as Part of STAF 2016, Proceedings. Vol. 9765. Springer. 2016. p. 36-51. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-42064-6_3

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

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