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DEPARS: Design Pattern Recognition System.

Authors: Sun, Te-Wei.;

DEPARS: Design Pattern Recognition System.

Abstract

The industry has widely accepted the concept of design patterns to promote quality design reuse in the recent years. However, there are several problems preventing design patterns being used efficiently and effectively. The design pattern recognition system, DEPARS, discussed in this dissertation relieves these problems and promotes design pattern reuse. DEPARS recognizes patterns in object models by matching to templates in the knowledge base. DEPARS arranges the templates in the knowledge base in a hierarchy such that templates close to the root of the hierarchy are the bases of the ones below. The hierarchy reduces DEPARS's matching effort because it narrows the search area. DEPARS provides information about the recognized patterns to designers. This information helps designers to apply appropriate patterns in designs. DEPARS has pattern mining capability. DEPARS recognizes new patterns that may be reusable in the future from existing designs. In addition, DEPARS also facilitates designers verifying the recurrence of proto-patterns by storing the proto-patterns in the knowledge base. Once the proto-patterns are in the knowledge base, DEPARS can recognize them in future designs and hence shows the recurrence of the proto-patterns. The dissertation presents the design and operation of DEPARS. The dissertation also reports and discusses the evaluation results of DEPARS. The evaluation shows promising results indicating that DEPARS is adequate for practical use.

Country
Canada
Keywords

Artificial Intelligence, Artificial Intelligence., 006

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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