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ICCSA
2003
Springer

A Probabilistic Model for Predicting Software Development Effort

9 years 3 months ago
A Probabilistic Model for Predicting Software Development Effort
—Recently, Bayesian probabilistic models have been used for predicting software development effort. One of the reasons for the interest in the use of Bayesian probabilistic models, when compared to traditional point forecast estimation models, is that Bayesian models provide tools for risk estimation and allow decision-makers to combine historical data with subjective expert estimates. In this paper, we use a Bayesian network model and illustrate how a belief updating procedure can be used to incorporate decision-making risks. We develop a causal model from the literature and, using a data set of 33 real-world software projects, we illustrate how decision-making risks can be incorporated in the Bayesian networks. We compare the predictive performance of the Bayesian model with popular nonparametric neural-network and regression tree forecasting models and show that the Bayesian model is a competitive model for forecasting software development effort.
Parag C. Pendharkar, Girish H. Subramanian, James
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where ICCSA
Authors Parag C. Pendharkar, Girish H. Subramanian, James A. Rodger
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