Abstract
Some study claim that Base Functional Components (BFCs) contributes to effort at different levels and thus using BFCs instead of Function Points (FP) is better for effort estimation. This study examined the claim with sound filtration and extra-sample error, which were lacked in the past study. As a result, we confirmed that BFCs-based modelings used in the past study was statistically inferior to a FP-based model. We also demonstrated that a BFCs-based model could become comparable to the FP-based model with suitable transformations for BFCs. The result contributes to understand the importance of transformations for BFCs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bouckaert, R.R.: Choosing between two learning algorithms based on calibrated tests. In: Proc. of ICML 2003, pp. 51–58 (2003)
Buglione, L., Gencel, C.: The significance of ifpug base functionality types in effort estimation: An empirical study. In: Proc. of ISMA5 2010 (2010)
Ferrucci, F., Gravino, C., Buglione, L.: Estimating web application development effort using cosmic: Impact of the base functional component types. In: Proc. of Smef 2010 (2010)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical learning: Data Mining, Inference, and Prediction. Springer (2009)
International Software Benchmarking Standards Group (ISBSG): ISBSG estimating, benchmarking and research suite release 11 (2004)
ISO: ISO/IEC 20926: Software Engineering – IFPUG 4.1 Unadjusted functional size measurement method – Counting practices manual. ISO (2003)
Jørgensen, M., Shepperd, M.: A systematic review of software development cost estimation studies. IEEE Trans. Softw. Eng. 33(1), 33–53 (2007)
Maxwell, K.D.: Applied Statistics for Software Managers. Prentice Hall, Inc. (2002)
McConell, S.: Software Estimation: Demystifying the Black Art. Microsoft Press (2006)
Mendes, E., Lokan, C.: Replicating studies on cross- vs single-company effort models using the isbsg database. Empirical Software Engineering 13(1), 3–37 (2008)
Miyazaki, Y., Takanou, A., Nozaki, H., Nakagawa, N., Okada, K.: Method to estimate parameter values in software prediction models. Information and Software Technology 33(3), 239–243 (1991)
Port, D., Korte, M.: Comparative studies of the model evaluation criterions MMRE and PRED in software cost estimation research. In: Proc. of ESEM 2008 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Amasaki, S., Yokogawa, T. (2012). A Study on Predictive Performance of Regression-Based Effort Estimation Models Using Base Functional Components. In: Dieste, O., Jedlitschka, A., Juristo, N. (eds) Product-Focused Software Process Improvement. PROFES 2012. Lecture Notes in Computer Science, vol 7343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31063-8_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-31063-8_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31062-1
Online ISBN: 978-3-642-31063-8
eBook Packages: Computer ScienceComputer Science (R0)