Towards efficient loading of change-based models

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Title of host publicationModelling Foundations and Applications - 14th European Conference, ECMFA 2018, Held as Part of STAF 2018, Proceedings
DateAccepted/In press - 9 Apr 2018
DateE-pub ahead of print (current) - 29 May 2018
Pages235-250
Number of pages16
PublisherSpringer-Verlag
Volume10890 LNCS
Original languageEnglish
ISBN (Electronic)978-3-319-92997-2
ISBN (Print)9783319929965

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

Abstract

This paper proposes and evaluates an efficient approach for loading models stored in a change-based format. The work builds on language-independent change-based persistence (CBP) of models conforming to object-oriented metamodelling architectures such as MOF and EMF, an approach which persists a model’s editing history rather than its current state. We evaluate the performance of the proposed loading approach and assess its impact on saving change-based models. Our results show that the proposed approach significantly improves loading times compared to the baseline CBP loading approach, and has a negligible impact on saving.

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© Springer International Publishing AG, part of Springer Nature 2018. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

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