Identifying System Patterns to Resolve Challenges in the Test and Evaluation Operation

Abstract

This research focuses on identification and description of patterns used in Test and Evaluation (T&E) operations. Patterns are defined as named and well-known problem/solution pairs that can be applied in new contexts, with advice on how to apply it in a novel situations and discussion of its trade-offs, implementations, and variations. They have a well established and used in software engineering, but have only recently been considered for systems engineering. In the Department of Defense (DOD), T&E is required for all acquisitions prior to transitioning into operations. As identified and described in this thesis, each of the patterns fits in one of the three categories: behavioral, creational, and functional. The research has identified eight named patterns to include: primary pattern, objective pattern, cost estimating pattern, scheduling pattern, risk management pattern, work acceptance process pattern, hazard control pattern, and test team pattern. The implementation of patterns by Department of Defense is expected to alleviate some of the common challenges encountered during T&E, provide a consistent higher quality and expectation, as well as efficiently use test infrastructure and personnel resources.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2013
Accession Number
ADA585943

Entities

People

  • Daniel K. Mutunga

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Department Of Defense
  • Engineering
  • Engineers
  • Governments
  • Identification
  • Literature Surveys
  • Personnel Management
  • Risk Management
  • Software Design
  • Software Development
  • Systems Engineering
  • Test And Evaluation
  • Test Equipment
  • Test Facilities
  • United States

Fields of Study

  • Computer science

Readers

  • Joint Military Operations and Doctrine.
  • Regression Analysis.
  • Software Engineering.