Affiliations: Department of Computer Science, California Polytechnic
State University, San Luis Obispo, CA 93407, U.S.A. | Tumbleweed Communication Corp., Redwood City, CA
94063, USA | New Jersey City University, NJ 07305, USA
Abstract: The construction of large software systems from existing components
requires efficient access to possibly large collections of such components. In
this paper, we present a content-based framework to organize this large
collection of components in a semi-automatic fashion, according to an
extensible user-defined ontology. Neural associative memories are used for
fast, similarity-based access. Relevant characteristics of components are
extracted and stored as a "signature" in such an associative memory, and during
retrieval the closest matches to the query are indicated in very short time. In
addition to content-based characteristics such as keywords, function and
variable names, comments, and the location of the component in the class
hierarchy, this method can be easily expanded to include usage characteristics,
resource requirements, or other task- or customer-specific criteria.
