Function Points Analysis: An Empirical Study of Its Measurement Processes
IEEE Transactions on Software Engineering
A Simulation Tool for Efficient Analogy Based Cost Estimation
Empirical Software Engineering
A Systematic Review of Software Development Cost Estimation Studies
IEEE Transactions on Software Engineering
Improving analogy-based software cost estimation by a resampling method
Information and Software Technology
Comparing cost prediction models by resampling techniques
Journal of Systems and Software
Empirical Software Engineering
On the value of outlier elimination on software effort estimation research
Empirical Software Engineering
Information and Software Technology
Hi-index | 0.00 |
Software Cost Estimation is the task of predicting the effort or productivity required to complete a software project. Two of the most known techniques appeared in literature so far are Regression Analysis and Estimation by Analogy. The results of the empirical studies show the lack of convergence in choosing the best prediction technique between the parametric Regression Analysis and the non-parametric Estimation by Analogy models. In this paper, we introduce the use of a semi-parametric model that achieves to incorporate some parametric information into a non-parametric model combining in this way regression and analogy. Furthermore, we demonstrate the procedure of building such a model on two well-known datasets and we present the comparative results based on the predictive accuracy of the new technique using several accuracy measures. We also perform statistical tests on the residuals in order to assess the improvement in the predictions attained through the new semi-parametric model in comparison to the accuracy of Regression Analysis and Estimation by Analogy when applied separately. Our results show that the semi-parametric model provides more accurate predictions than each one of the parametric and non-parametric approaches.