Incremental evaluation of model queries over EMF models: A tutorial on EMF-IncQuery

Gábor Bergmann, Ákos Horváth, István Ráth, Dániel Varró

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

4 Citations (Scopus)

Abstract

Model driven development platforms such as the industry leader Eclipse Modeling Framework (EMF) greatly benefit from pattern matching, as it supports various usecases including model validation, model transformation, code generation and domain specific behaviour simulation. Pattern matching is a search for model elements conforming to a given pattern that describes their arrangement and properties, e.g. finding a violation of a complex well-formedness constraint of a domain specific modeling language.

Original languageEnglish
Title of host publicationModelling Foundations and Applications - 7th European Conference, ECMFA 2011, Proceedings
Pages389-390
Number of pages2
DOIs
Publication statusPublished - Jun 22 2011
Event7th European Conference on Modelling Foundations and Applications, ECMFA 2011 - Birmingham, United Kingdom
Duration: Jun 6 2011Jun 9 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6698 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th European Conference on Modelling Foundations and Applications, ECMFA 2011
CountryUnited Kingdom
CityBirmingham
Period6/6/116/9/11

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Keywords

  • EMF
  • incremental pattern matching
  • model query

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Bergmann, G., Horváth, Á., Ráth, I., & Varró, D. (2011). Incremental evaluation of model queries over EMF models: A tutorial on EMF-IncQuery. In Modelling Foundations and Applications - 7th European Conference, ECMFA 2011, Proceedings (pp. 389-390). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6698 LNCS). https://doi.org/10.1007/978-3-642-21470-7_32