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Abstract

Techniques for factoring one or more source graphs into a composite graph containing nodes representing analogous elements of the source graphs and a variability graph containing nodes representing differences in the source graphs. The composite graph is made by taking analogous input trees from the source graphs and traversing the trees from top to bottom looking for nodes in each tree at each level that are analogous to the nodes at that level in the other input trees. The sets of analogous nodes are found by first automatically correlating the nodes in the level currently being examined. Correlation may, for example, be based on similar values of a property of the nodes being correlated. Representations of the sets of correlated nodes are then displayed to a user, who indicates which sets of correlated nodes are in fact analogous. The user may also indicate that the nodes in a set of correlated nodes are not analogous or that nodes that were found by the automatic correlation not to be autonomous are in fact. The analogous nodes are allocated to a corresponding node at a corresponding level in the composite graph; the other nodes are allocated to a set of anomalous nodes. One application for the techniques is managing graphs which are models of catalogs of items.

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