Many of the problems of simulating and rendering complex systems of non-rigid objects can be minimized by describing the geometry and dynamics separately, using representations optimized for either one or the other, and then coupling these representations together. We describe a system which uses polynomial deformation mappings to couple a vibration-mode ("modal") representation of object dynamics together with volumetric models of object geometry. By use of such a hybrid representation we have been able to gain up to two orders of magnitude in efficiency, control temporal aliasing, and obtain simple, closed-form solutions to common (non-rigid) inverse dynamics problems. Further, this approach to dynamic simulation naturally lends itself to the emphasis and exaggeration techniques used in traditional animation.

Modern deep packet inspection systems use regular expressions to define various patterns of interest in network data streams. Deterministic Finite Automata (DFA) are commonly used to parse regular expressions. DFAs are fast, but can require prohibitively large amounts of memory for patterns arising in network applications. Traditional DFA table compression only slightly reduces the memory required and requires an additional memory access per input character. Alternative representations of regular expressions, such as NFAs and Delayed Input DFAs (D 2 FA) require less memory but sacrifice throughput. In this paper we introduce the Content Addressed Delayed Input DFA (CD 2 FA), which provides a compact representation of regular expressions that match the throughput of traditional uncompressed DFAs. A CD 2 FA addresses successive states of a D 2 FA using their content, rather than a "content-less" identifier. This makes selected information available earlier in the state traversal process, which makes it possible to avoid unnecessary memory accesses. We demonstrate that such content-addressing can be effectively used to obtain automata that are very compact and can achieve high throughput. Specifically, we show that for an application using thousands of patterns defined by regular expressions, CD 2 FAs use as little as 10% of the space required by a conventional compressed DFA, and match the throughput of an uncompressed DFA.

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Abstract. Data in object-oriented programming is organized in a hierarchy of classes. The problem of object-oriented pattern matching is how to explore this hierarchy from the outside. This usually involves classifying objects by their run-time type, accessing their members, or determining some other characteristic of a group of objects. In this paper we compare six different pattern matching techniques: object-oriented decomposition, visitors, type-tests/type-casts, typecase, case classes, and extractors. The techniques are compared on nine criteria related to conciseness, maintainability and performance. The paper introduces case classes and extractors as two new pattern-matching methods and shows that their combination works well for all of the established criteria.

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