by Holger Giese, Stephan Hildebrandt
Abstract:
Model-driven software development requires techniques to consistently propagate modifications between different related models to realize its full potential. For large-scale models, efficiency is essential in this respect. In this paper, we present an improved model synchronization algorithm based on triple graph grammars that is highly efficient and, therefore, can also synchronize large-scale models sufficiently fast. We can show, that the overall algorithm has optimal complexity if it is dominating the rule matching and further present extensive measurements that show the efficiency of the presented model transformation and synchronization technique.
Reference:
Efficient Model Synchronization of Large-Scale Models (Holger Giese, Stephan Hildebrandt), Technical report 28, Hasso Plattner Institute at the University of Potsdam, 2009.
Bibtex Entry:
@TechReport{GH2009,
AUTHOR = {Giese, Holger and Hildebrandt, Stephan},
TITLE = {{Efficient Model Synchronization of Large-Scale Models}},
YEAR = {2009},
NUMBER = {28},
INSTITUTION = {Hasso Plattner Institute at the University of Potsdam},
PDF = {uploads/pdf/GH2009.pdf},
ABSTRACT = {Model-driven software development requires techniques to consistently propagate modifications between different related models to realize its full potential. For large-scale models, efficiency is essential in this respect. In this paper, we present an improved model synchronization algorithm based on triple graph grammars that is highly efficient and, therefore, can also synchronize large-scale models sufficiently fast. We can show, that the overall algorithm has optimal complexity if it is dominating the rule matching and further present extensive measurements that show the efficiency of the presented model transformation and synchronization technique.}
}