First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) A Comparison of Techniques for Web Effort Estimation Madrid, Spain September 20-September 21 ISBN: 0-7695-2886-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.14
OBJECTIVE - The objective of this paper is to extend the work by Mendes [15], and to compare four techniques for Web effort estimation to identify which one provides best prediction accuracy. METHOD - We employed four effort estimation techniques - Bayesian networks (BN), forward stepwise regression (SWR), case-based reasoning (CBR) and Classification and regression trees (CART) to obtain effort estimates. The dataset employed was of 150 Web projects from the Tukutuku dataset. RESULTS - Results showed that predictions obtained using a BN were significantly superior to those using other techniques. CONCLUSIONS - A model that incorporates the uncertainty inherent in effort estimation, can outperform other commonly used techniques, such as those used in this study.
Citation:
Emilia Mendes, "A Comparison of Techniques for Web Effort Estimation," esem, pp.334-343, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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