Collaborative editing of EMF/Ecore meta-models and models: Conflict detection, reconciliation, and merging in DiCoMEF

Research output: Contribution to journalSpecial issuepeer-review

Abstract

Despite the fact that Domain Specific Modeling tools are becoming very powerful and more frequently used, the support for their cooperation has not reached its full strength, and demand for model management is growing. In cooperative work, the decision agents are semi-autonomous and therefore a solution for reconciliating DSM after a concurrent evolution is needed. Conflict detection and reconciliation are important steps for merging of concurrently evolved (meta)models in order to ensure collaboration. In this work, we present a conflict detection, reconciliation and merging framework for concurrently evolved meta-models and models. Additionally, we formally specify the EMF Ecore meta-model into set constructs that help to analyze the (meta)model and operations performed on it.

Original languageEnglish
JournalScience of Computer Programming
DOIs
Publication statusAccepted/In press - 2015

Keywords

  • Collaborative modeling
  • Conflict detection
  • DSML
  • EMF
  • Merging

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