Towards Scalable Validation of Low-Code System Models: Mapping EVL to VIATRA Patterns

Qurat Ul Ain Ali, Benedek Horváth, Dimitris Kolovos, Konstantinos Barmpis, Ákos Horváth

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

Abstract

Adoption of low-code engineering in complex enterprise applications also increases the size of the underlying models. In such cases, the increasing complexity of the applications and the growing size of the underlying artefacts, various scalability
challenges might arise for low-code platforms. Task-specific programming languages, such as OCL and EOL, are tailored to manage the underlying models. Existing model management languages have significant performance impact when it comes to
complex queries operating over large-scale models reaching magnitudes of millions of elements in size. We propose an approach for automatically mapping expressions in Epsilon validation programs to VIATRA graph patterns to make the validation of
large-scale low-code system models scalable by leveraging the incremental execution engine of VIATRA. Finally, we evaluate the performance of the proposed approach on large Java models of the Eclipse source code. Our results show performance speed-up
up to 1481x compared to the sequential execution in Epsilon.
Original languageEnglish
Title of host publicationCompanion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021
PublisherIEEE
Pages83-87
Number of pages5
ISBN (Electronic)9781665424844
DOIs
Publication statusPublished - 20 Dec 2021
Event24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021 - Virtual, Online, Japan
Duration: 10 Oct 202115 Oct 2021

Publication series

NameCompanion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021

Conference

Conference24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021
Country/TerritoryJapan
CityVirtual, Online
Period10/10/2115/10/21

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS This work was partially funded by the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curiegrant agreement No 813884, and the National Research, Development and Innovation Fund of Hungary, financed under the 2019-2.1.1-EUREKA-2019-00001 funding scheme. The authors are grateful for the valuable feedback of the anonymous reviewers and Géza Kulcsár.

Publisher Copyright:
© 2021 IEEE.

Keywords

  • static analysis
  • model querying
  • graph patterns
  • scalability

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