An Experiment in Software Development Risk Information Analysis.

Abstract

This report summarizes the results of an experiment that uses terminological structures derived from the application of knowledge summarization, analysis, and visualization (K-SAV) technology to textual data from the Software Engineering Risk Repository (SERR) resident at the Software Engineering Institute. This study evaluates the use of several tools including shared word clustering (Monarch 94) and a co-word analysis software program, leximappe Tell 92. The experiment seeks to determine whether an application of co-word analysis to baseline risk assessment data would enable a reduction of the information load while simultaneously providing a succinct but encompassing picture of the risk information within the program. This study is based upon a somewhat limited data set. Nevertheless, the results of this investigation are encouraging and suggest that there may be value and potential for the effective use of co-word analysis and K-SAV technology more generally in risk management. Additional investigations are underway to confirm, alter, or challenge the results.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1995
Accession Number
ADA302320

Entities

People

  • David P. Gluch
  • Ira Monarch

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Business Administration
  • Classification
  • Clustering
  • Data Sets
  • Debugging
  • Department Of Defense
  • Engineering
  • Governments
  • Language
  • Natural Language Processing
  • Natural Languages
  • Risk
  • Risk Analysis
  • Risk Management
  • Software Development
  • United States

Fields of Study

  • Computer science
  • Engineering

Readers

  • Research Science/Academic Research
  • Software Engineering.
  • Theoretical Analysis.