Analysis Techniques for Use with the Extended SDM Model.

Abstract

Complex design problems are characterized by a multitude of competing requirements. System designers frequently find the scope of the problem beyond their conceptual abilities, and attempt to cope with this difficulty by decomposing the original design problem into smaller, more manageable sub-problems. Functional requirements form a key interface between the users of a system and its designers. In this research effort, a systematic approach has been proposed for the decomposition of the overall set of functional requirements into sub-problems to form a design structure that will exhibit the key characteristics of good design: strong coupling within sub-problems, and week coupling between them. Recent work in the Systematic Design Methodology project has led to certain extensions to the basic representational model used therein. This report presents new analytical mechanisms that may be used to execute decomposition analyses in the context of the extended model. Included are new methods for calculating inter-requirement similarities, for measuring decomposition goodness, and for generating clustering hierarchies. As well, some new hierarchical clustering tools are presented, with examples. A complete analysis of a 22-node design problem is presented, and compared with results obtained for the same problem in earlier work using the original SDM model.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1979
Accession Number
ADA071647

Entities

People

  • S. E. Madnick
  • S. L. Huff

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Case Studies
  • Complex Systems
  • Computer Programs
  • Computers
  • Database Management Systems
  • Databases
  • Decision Support Systems
  • Hierarchies
  • Information Systems
  • Management Information Systems
  • Software Design
  • Software Development
  • Systems Engineering

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Software Engineering.