A Bayesian approach to diagram matching
with application to architectural models;
Proceedings of the 28th international
conference on Software Engineering 2006;
ACM Digital Library
high quality correspondences
Abstract: IT system architectures, as well as other
systems, are often described by formal models or informal
diagrams. In practice, there are often a number of
versions of a model, e.g. for different views of a system,
divergent variants, or a series of revisions.
Understanding how versions of a model correspond or differ
is crucial, yet little work has been done on automated
assistance for matching models and diagrams.
We have designed a framework based on Bayesian methods
for finding these correspondences automatically. We
represent models and diagrams as graphs whose nodes have
attributes such as name, type, connections, 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.