Software Acquisition Patterns of Failure and How to Recognize Them

Abstract

In systems today, software provides substantial portions of capability and performance. In many Department of Defense (DoD) acquisitions, however, software too often is a minor consideration when the early and most constraining decisions about program cost, schedule, and behavior are made (i.e., prior to Milestone A). These decisions manifest themselves in the acquisition strategy, the system and software architecture, and ultimately in the deployed system. Based on our experience with large programs, we have identified seven patterns of failure that lead to misalignment between the software architecture and the acquisition strategy, leading to program restarts, cancellations, or other failures. We describe the characteristics of these patterns of failure and relate them to weak or missing relationships between key artifacts relationships that should exist even at an early stage of the life cycle. In this paper, we focus on those artifacts that relate to the expression and analysis of business goals. We present early results in the development of acquisition quality attributes (analogous to software quality attributes) and how these attributes relate to acquisition strategies. We conclude with some speculation on what is needed to avoid the failure patterns.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2013
Accession Number
ADA584766

Entities

People

  • Cecilia Albert
  • David J. Carney
  • Lisa Brownsword
  • Patrick R.H. Place

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Artifacts
  • Cancellation
  • Commerce
  • Contractors
  • Contracts
  • Department Of Defense
  • Engineering
  • Engineers
  • Governments
  • Life Cycles
  • Misalignment
  • Procurement
  • Software Design
  • Software Development
  • Warfare

Fields of Study

  • Computer science
  • Engineering

Readers

  • Life Cycle Cost Analysis
  • Parallel and Distributed Computing.
  • Systems Analysis and Design