A M2MC based approach for mapping two ADL models
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
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IT system architectures and many other kinds of structured artifacts are often described by formal models or informal diagrams. In practice, there are often a number of versions of a model or diagram, such as a series of revisions, divergent variants, or multiple views of a system. Understanding how versions correspond or differ is crucial, and thus, automated assistance for matching models and diagrams is essential. We have designed a framework for finding these correspondences automatically based on Bayesian methods. We represent models and diagrams as graphs whose nodes have attributes such as name, type, connections to other nodes, and containment relations, and we have developed probabilistic models for rating the quality of candidate correspondences based on various features of the nodes in the graphs. Given the probabilistic models, we can find high-quality correspondences using search algorithms. Preliminary experiments focusing on architectural models suggest that the technique is promising.