Abstract
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.
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Valdés, F., Abran, A. (2010). Comparing the Estimation Performance of the EPCU Model with the Expert Judgment Estimation Approach Using Data from Industry. In: Lee, R., Ormandjieva, O., Abran, A., Constantinides, C. (eds) Software Engineering Research, Management and Applications 2010. Studies in Computational Intelligence, vol 296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13273-5_15
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DOI: https://doi.org/10.1007/978-3-642-13273-5_15
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