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The Evaluation of Weighted Moving Windows for Software Effort Estimation

  • Conference paper
Product-Focused Software Process Improvement (PROFES 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7983))

Abstract

In construction of an effort estimation model, it seems effective to use a window of training data so that the model is trained with only recent projects. Considering the chronological order of projects within the window, and weighting projects according to their order within the window, may also affect estimation accuracy. In this study, we examined the effects of weighted moving windows on effort estimation accuracy. We compared weighted and non-weighted moving windows under the same experimental settings. We confirmed that weighting methods significantly improved estimation accuracy in larger windows, though the methods also significantly worsened accuracy in smaller windows. This result contributes to understanding properties of moving windows.

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Author information

Authors and Affiliations

  1. Department of Systems Engineering, Okayama Prefectural University, Japan

    Sousuke Amasaki

  2. School of Engineering and Information Technology, UNSW Canberra, Australia

    Chris Lokan

Authors
  1. Sousuke Amasaki
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  2. Chris Lokan
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Editor information

Editors and Affiliations

  1. Fraunhofer IESE, Fraunhofer Platz 1, 67663, Kaiserslautern, Germany

    Jens Heidrich  & Andreas Jedlitschka  & 

  2. University of Oulu, P.O. Box 3000, 90014, Oulu, Finland

    Markku Oivo

  3. University of Bari, Via E. Orabona 4, 70125, Bari, Italy

    Maria Teresa Baldassarre

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© 2013 Springer-Verlag Berlin Heidelberg

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Amasaki, S., Lokan, C. (2013). The Evaluation of Weighted Moving Windows for Software Effort Estimation. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds) Product-Focused Software Process Improvement. PROFES 2013. Lecture Notes in Computer Science, vol 7983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39259-7_18

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  • DOI: https://doi.org/10.1007/978-3-642-39259-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39258-0

  • Online ISBN: 978-3-642-39259-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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