The Community for Technology Leaders
Knowledge-Based Software Engineering Conference (1995)
Boston, Massachusetts
Nov. 12, 1995 to Nov. 15, 1995
ISSN: 1068-3062
ISBN: 0-8186-7204-8
pp: 131
J. Penix , Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
P. Baraona , Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
P. Alexander , Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
Automated assistance for software component reuse involves supporting retrieval, adaptation and verification of software components. The informality of feature-based software classification schemes is an impediment to formally verifying the reusability of a software component. The use of formal specifications to model and retrieve reusable components alleviates the informality, but the formal reasoning required for retrieval introduces questions of scalability. To provide scalability, current retrieval systems resort to syntactic classification at some level of abstraction, abandoning the semantic information provided by the specification. We propose a methodology that shifts the overhead of formal reasoning from the retrieval to the classification phase of reuse. Software components are classified using semantic features that are derived from their formal specification. Retrieval of functionally similar components can then be accomplished based on the stored feature sets. Formal verification can be applied to precisely determine the reusability of the set of similar components.
formal specification; formal verification; software reusability; computer aided software engineering; inference mechanisms; reusable component retrieval; reusable component classification; semantic features; automated assistance; software component reuse; software component adaptation; reusability; formal specifications; formal reasoning; scalability; syntactic classification; abstraction; semantic information; stored feature sets; formal verification

P. Alexander, J. Penix and P. Baraona, "Classification and retrieval of reusable components using semantic features," Knowledge-Based Software Engineering Conference(KBSE), Boston, Massachusetts, 1995, pp. 131.
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