Abstract
Several studies in software effort estimation have found that it can be effective to use a window of recent projects as training data for building an effort estimation model. Windows can be defined as having a fixed size (containing a fixed number of projects), or as having a fixed duration. A recent study extended the idea of windows, by weighting projects differently according to their order within the window, and found that weighted moving windows could significantly improve estimation accuracy. That study used fixed-size windows. This study examines the effect on effort estimation accuracy of weighted moving windows that are based on fixed duration. We compare weighted and unweighted moving windows under the same experimental settings. Weighting methods are found to improve estimation accuracy significantly in larger windows, and the methods also significantly improved accuracy in smaller windows in terms of MRE. This result contributes further to understanding properties of moving windows.
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References
Lokan, C., Mendes, E.: Applying moving windows to software effort estimation. In: Proc. of ESEM 2009, pp. 111–122 (2009)
Lokan, C., Mendes, E.: Investigating the Use of Duration-Based Moving Windows to Improve Software Effort Prediction. In: Proc. of APSEC 2012, pp. 818–827 (2012)
Amasaki, S., Lokan, C.: The evaluation of weighted moving windows for software effort estimation. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds.) PROFES 2013. LNCS, vol. 7983, pp. 214–228. Springer, Heidelberg (2013)
Auer, M., Biffl, S.: Increasing the accuracy and reliability of analogy-based cost estimation with extensive project feature dimension weighting. In: Proc. of ISESE 2004, pp. 147–155. IEEE (2004)
Mendes, E., Lokan, C.: Investigating the use of chronological splitting to compare software cross-company and single-company effort predictions: A replicated study. In: Proc. of EASE 2009 (2009)
Keung, J.W., Kitchenham, B.A., Jeffery, D.R.: Analogy-X: Providing Statistical Inference to Analogy-Based Software Cost Estimation. IEEE Trans. Softw. Eng. 34(4), 471–484 (2008)
Li, J., Ruhe, G.: Analysis of attribute weighting heuristics for analogy-based software effort estimation method AQUA+. Empir. Softw. Eng. 13(1), 63–96 (2007)
Maxwell, K.D.: Applied Statistics for Software Managers. Prentice Hall (2002)
Loader, C.: Local Regression and Likelihood. Statistics and Computing. Springer (1999)
Tabachnick, B.G., Fidell, L.S.: Using Multivariate Statistics. Harper-Collins (1996)
Tibshirani, R.: Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B, 267–288 (1996)
Port, D., Korte, M.: Comparative studies of the model evaluation criterions mmre and pred in software cost estimation research. In: Proc. of ESEM 2008. ACM (2008)
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Amasaki, S., Lokan, C. (2014). The Effects of Gradual Weighting on Duration-Based Moving Windows for Software Effort Estimation. In: Jedlitschka, A., Kuvaja, P., Kuhrmann, M., Männistö, T., Münch, J., Raatikainen, M. (eds) Product-Focused Software Process Improvement. PROFES 2014. Lecture Notes in Computer Science, vol 8892. Springer, Cham. https://doi.org/10.1007/978-3-319-13835-0_5
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DOI: https://doi.org/10.1007/978-3-319-13835-0_5
Publisher Name: Springer, Cham
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