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Annals of Software Engineering

, Volume 10, Issue 1–4, pp 177–205 | Cite as

Software development cost estimation approaches — A survey

  • Barry Boehm
  • Chris Abts
  • Sunita Chulani
Article

Abstract

This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertise‐based techniques, learning‐oriented techniques, dynamics‐based models, regression‐based models, and composite‐Bayesian techniques for integrating expertise‐based and regression‐based models. Experience to date indicates that neural‐net and dynamics‐based techniques are less mature than the other classes of techniques, but that all classes of techniques are challenged by the rapid pace of change in software technology. The primary conclusion is that no single technique is best for all situations, and that a careful comparison of the results of several approaches is most likely to produce realistic estimates.

Keywords

Software Project Ordinary Little Square Method Work Breakdown Structure Effort Multiplier Ordinary Little Square Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Barry Boehm
    • 1
  • Chris Abts
    • 1
  • Sunita Chulani
    • 2
  1. 1.University of Southern CaliforniaLos AngelesUSA
  2. 2.IBM ResearchSan JoseUSA E‐mail

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