Automated Metamodel/Model Co-Evolution: A Search-Based Approach

Wael Kessentini, Houari Sahraoui, Manuel Wimmer

Research output: Contribution to journalArticlepeer-review

Abstract

Metamodels evolve over time to accommodate new features, improve existing designs, and fix errors identified in previous releases. One of the obstacles that may limit the adaptation of new metamodels by developers is the extensive manual changes that have been applied to migrate existing models. Recent studies addressed the problem of automating the metamodel/model co-evolution based on manually defined migration rules. The definition of these rules requires the list of changes at the metamodel level which are difficult to fully identify. Furthermore, different possible alternatives may be available to translate a metamodel change to a model change. Thus, it is hard to generalize these co-evolution rules.
Original languageEnglish
Pages (from-to)49-67
Number of pages19
JournalInformation and Software Technology
Volume106
DOIs
Publication statusPublished - Feb 2019

Fields of science

  • 202017 Embedded systems
  • 102002 Augmented reality
  • 102006 Computer supported cooperative work (CSCW)
  • 102015 Information systems
  • 102020 Medical informatics
  • 102022 Software development
  • 102034 Cyber-physical systems
  • 201132 Computational engineering
  • 201305 Traffic engineering
  • 207409 Navigation systems
  • 502032 Quality management
  • 502050 Business informatics
  • 503015 Subject didactics of technical sciences

JKU Focus areas

  • Digital Transformation

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