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The methodology of multi-viewpoint clustering analysisOne of the greatest challenges facing the software engineering community is the ability to produce large and complex computer systems, such as ground support systems for unmanned scientific missions, that are reliable and cost effective. In order to build and maintain these systems, it is important that the knowledge in the system be suitably abstracted, structured, and otherwise clustered in a manner which facilitates its understanding, manipulation, testing, and utilization. Development of complex mission-critical systems will require the ability to abstract overall concepts in the system at various levels of detail and to consider the system from different points of view. Multi-ViewPoint - Clustering Analysis MVP-CA methodology has been developed to provide multiple views of large, complicated systems. MVP-CA provides an ability to discover significant structures by providing an automated mechanism to structure both hierarchically (from detail to abstract) and orthogonally (from different perspectives). We propose to integrate MVP/CA into an overall software engineering life cycle to support the development and evolution of complex mission critical systems.
Document ID
19940034747
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Mehrotra, Mala
(Pragati Synergetic Research, Inc. Yorktown, VA, United States)
Wild, Chris
(Old Dominion Univ. Norfolk, VA, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1993
Publication Information
Publication: In: AIAA Computing in Aerospace Conference, 9th, San Diego, CA, Oct. 19-21, 1993, Technical Papers. Pt. 1 (A94-11401 01-62)
Publisher: American Institute of Aeronautics and Astronautics
Subject Category
Computer Programming And Software
Report/Patent Number
AIAA PAPER 93-4460
Accession Number
94A11402
Funding Number(s)
CONTRACT_GRANT: NAS9-18706
Distribution Limits
Public
Copyright
Other

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