Building an expert-based web effort estimation model using bayesian networks

  • Authors:
  • Emilia Mendes;Carmel Pollino;Nile Mosley

  • Affiliations:
  • Computer Science department, The University of Auckland, Auckland, NZ;The Fenner School of Environment and Society, The Australian National University, Canberra, Australia;MetriQ Ltd., Oneroa, Auckland, NZ

  • Venue:
  • EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
  • Year:
  • 2009

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Abstract

OBJECTIVE - The objective of this paper is to describe a case study where Bayesian Networks (BNs) were used to construct an expert-based Web effort model. METHOD - We built a single-company BN model solely elicited from expert knowledge, where the domain expert was an experienced Web project manager from a small Web company in Auckland, New Zealand. This model was validated using data from eight past finished Web projects. RESULTS - The BN model has to date been successfully used to estimate effort for four Web projects, providing effort estimates superior to those based solely on expert opinion. CONCLUSIONS - Our results suggest that, at least for the Web Company that participated in this case study, the use of a model that allows the representation of uncertainty, inherent in effort estimation, can outperform expert-based estimates. Another five companies have also benefited from using Bayesian Networks, with very promising results.