Towards an Effective Analysis Pattern Retrieval

  • Maria João Ferreira
  • Pericles Loucopoulos
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 732)


Since the introduction of patterns in Computer Science, a large number of libraries of patterns for different domains have been identified. In most cases these patterns are represented in a ‘flat’ fashion making their use difficult especially when there is a large number of patterns to consider in a particular application. In this paper we propose an analysis pattern retrieval (APR) approach under a classification schema in order to enable the automatic re-use of analysis patterns. The proposed classification scheme associates a problem to a set of pre-defined terms whereas the retrieval approach based on a Boolean model provides the necessary support to help a designer to locate and select analysis patterns that better solve the conceptual problem that he has in hands. An APR approach under a classification schema has the potential to make large analysis patterns collections easier to use and understand.


Business Process Classification Scheme Analysis Pattern Conjunctive Normal Form Information Retrieval System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Maria João Ferreira
    • 1
  • Pericles Loucopoulos
    • 2
  1. 1.Departamento de InformáticaUniversidade PortucalensePortoPortugal
  2. 2.Department of ComputationUMISTManchesterUK

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