Comparing the Estimation Performance of the EPCU Model with the Expert Judgment Estimation Approach Using Data from Industry

  • Francisco Valdés
  • Alain Abran
Part of the Studies in Computational Intelligence book series (SCI, volume 296)


Software project estimates are more useful when made early in the project life cycle: this implies that these estimates are to be made in a highly uncertain environment with information that is vague and incomplete.

To tackle these challenges in practice, the estimation method most used at this early stage is the Expert Judgment Estimation approach. However, there are a number of problems with it, such as the fact that the expertise is specific to the people and not to the organization, and the fact that this intuitive estimation expertise is neither well described nor well understood; in addition, the expertise is difficult to assess and cannot be replicated systematically.

Estimation of Projects in Contexts of Uncertainty (EPCU) is an estimation method based on fuzzy logic that mimics the way experts make estimates. This paper describes the experiment designed and carried out to compare the performance of the EPCU model against the Expert Judgment Estimation approach using data from industry projects.


EPCU Estimation Projects Uncertainty Contexts Fuzzy Sets Expert Judgment Estimation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Francisco Valdés
    • 1
  • Alain Abran
    • 1
  1. 1.Dept. of Software EngineeringÉcole de Technologie SupérieureMontréalCanada

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