Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T08:44:38.432Z Has data issue: false hasContentIssue false

A generic ontology-based approach for requirement analysis and its application in network management software

Published online by Cambridge University Press:  01 January 1999

CHAU-YOUNG IVAN LIN
Affiliation:
Department of Electronic Engineering, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei, Taiwan
CHENG-SEEN HO
Affiliation:
Department of Electronic Engineering, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei, Taiwan

Abstract

This paper describes a generic ontology-based approach that eases the requirement analysis (RA) work. The approach enables the user to derive method-specific RA tools for different applications. The derivation process is based on a unified framework that contains a software methodology ontology and a knowledge acquisition ontology. The former contains a library of software RA methods and a set of modeling support entities, which use the library to construct methodological knowledge. The latter contains a library of knowledge acquisition techniques and a set of acquisition support entities, which work on the library, guided by the generated methodological knowledge, to extract domain knowledge. The generated methodological knowledge, coupled with the domain knowledge, forms the RA tools. We have demonstrated the use of the approach by deriving an RA tool to assist the system analyst to acquire and formalize a requirement specification for a network management system. This approach facilitates the integrating, sharing, and reuse of software methodologies and knowledge acquisition techniques and alleviates the problems associated with the correct generation of requirement specification for different domains.

Type
Research Article
Copyright
1999 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)