Parallel model validation with epsilon

Sina Madani*, Dimitrios S. Kolovos, Richard F. Paige

*Corresponding author for this work

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

Abstract

Traditional model management programs, such as transformations, often perform poorly when dealing with very large models. Although many such programs are inherently parallelisable, the execution engines of popular model management languages were not designed for concurrency. We propose a scalable data and rule-parallel solution for an established and feature-rich model validation language (EVL). We highlight the challenges encountered with retro-fitting concurrency support and our solutions to these challenges. We evaluate the correctness of our implementation through rigorous automated tests. Our results show up to linear performance improvements with more threads and larger models, with significantly faster execution compared to interpreted OCL.

Original languageEnglish
Title of host publicationModelling Foundations and Applications - 14th European Conference, ECMFA 2018, Held as Part of STAF 2018, Proceedings
PublisherSpringer
Pages115-131
Number of pages17
Volume10890 LNCS
ISBN (Print)9783319929965
DOIs
Publication statusPublished - 25 Jun 2018
Event14th European Conference on Modelling Foundations and Applications, ECMFA 2018 Held as Part of STAF 2018 - Toulouse, France
Duration: 26 Jun 201828 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10890 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference14th European Conference on Modelling Foundations and Applications, ECMFA 2018 Held as Part of STAF 2018
Country/TerritoryFrance
CityToulouse
Period26/06/1828/06/18

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