Abstract. Approximate geometric models, e.g. as created by reverse engineering, describe the approximate shape of an object, but do not record the underlying design intent. Automatically inferring geometric aspects of the design intent, represented by feature trees and geometric constraints, enhances the utility of such models for downstream tasks. One approach to design intent detection in such models is to decompose them into regularity features. Geometric regularities such as symmetries may then be sought in each regularity feature, and subsequently be combined into a global, consistent description of the model's geometric design intent. This paper describes a systematic approach for finding such regularity features based on recovering broken symmetries in the model. The output is a tree of regularity features for subsequent use in regularity detection and selection. Experimental results are given to demonstrate the operation and efficiency of the algorithm.

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This paper describes a Wrapper Generator for wrapping high performance legacy codes as Java/CORBA components for use in a distributed component-based problemsolving environment. Using the Wrapper Generator we have automatically wrapped an MPI-based legacy code as a single CORBA object, and implemented a problemsolving environment for molecular dynamic simulations. Performance comparisons between runs of the CORBA object and the original legacy code on a cluster of workstations and on a parallel computer are also presented.

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