Local and global relational consistency
Theoretical Computer Science - Special issue: principles and practice of constraint programming
The PROGRES approach: language and environment
Handbook of graph grammars and computing by graph transformation
Graph Pattern Matching in PROGRES
Selected papers from the 5th International Workshop on Graph Gramars and Their Application to Computer Science
Story Diagrams: A New Graph Rewrite Language Based on the Unified Modeling Language and Java
TAGT'98 Selected papers from the 6th International Workshop on Theory and Application of Graph Transformations
AGG: A Tool Environment for Algebraic Graph Transformation
AGTIVE '99 Proceedings of the International Workshop on Applications of Graph Transformations with Industrial Relevance
VIATRA " Visual Automated Transformations for Formal Verification and Validation of UML Models
Proceedings of the 17th IEEE international conference on Automated software engineering
Adaptive Graph Pattern Matching for Model Transformations using Model-sensitive Search Plans
Electronic Notes in Theoretical Computer Science (ENTCS)
Model transformation language MOLA
MDAFA'03 Proceedings of the 2003 European conference on Model Driven Architecture: foundations and Applications
GrGen: a fast SPO-based graph rewriting tool
ICGT'06 Proceedings of the Third international conference on Graph Transformations
Complementary use case scenario representations based on domain vocabularies
MODELS'07 Proceedings of the 10th international conference on Model Driven Engineering Languages and Systems
| Hi-index | 0.00 |
This paper addresses the pattern matching problem for model transformation languages. Despite being an NP-complete problem, the pattern matching can be solved efficiently in typical areas of application. Prediction of actual cardinalities of model elements is the key to sufficient efficiency. The existing approaches aquire the actual cardinalities using complex run-time model analysis or using analysis of metamodel where the required information is poorly supplied. In the paper we show how the deeper understanding of domain which is targeted by model transformation language can dramatically reduce the complexity of pattern matching implementation. We propose a simple pattern matching algorithm for model transformation MOLA which is efficient for tasks related to the model driven software development. Additionaly a metamodel annotation mechanism is proposed. It refines the existing means of metamodelling by adding new classes of cardinalites. They make more efficient the pattern matching algorithms which do not use the complex run-time analysis.