Foundations for Streaming Model Transformations by Complex Event Processing

István Dávid, István Ráth, Dániel Varró

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Streaming model transformations represent a novel class of transformations to manipulate models whose elements are continuously produced or modified in high volume and with rapid rate of change. Executing streaming transformations requires efficient techniques to recognize activated transformation rules over a live model and a potentially infinite stream of events. In this paper, we propose foundations of streaming model transformations by innovatively integrating incremental model query, complex event processing (CEP) and reactive (event-driven) transformation techniques. Complex event processing allows to identify relevant patterns and sequences of events over an event stream. Our approach enables event streams to include model change events which are automatically and continuously populated by incremental model queries. Furthermore, a reactive rule engine carries out transformations on identified complex event patterns. We provide an integrated domain-specific language with precise semantics for capturing complex event patterns and streaming transformations together with an execution engine, all of which is now part of the Viatra reactive transformation framework. We demonstrate the feasibility of our approach with two case studies: one in an advanced model engineering workflow; and one in the context of on-the-fly gesture recognition.

Original languageEnglish
Pages (from-to)135-162
Number of pages28
JournalSoftware and Systems Modeling
Volume17
Issue number1
DOIs
Publication statusPublished - Feb 1 2018

Keywords

  • Change-driven transformations
  • Complex event processing
  • Live models
  • Reactive transformations
  • Streaming model transformations

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation

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