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Classification and Prediction of Software Cost through Fuzzy Decision Trees

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Enterprise Information Systems (ICEIS 2009)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 24))

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Abstract

This work addresses the issue of software effort prediction via fuzzy decision trees generated using historical project data samples. Moreover, the effect that various numerical and nominal project characteristics used as predictors have on software development effort is investigated utilizing the classification rules extracted. The approach attempts to classify successfully past project data into homogeneous clusters to provide accurate and reliable cost estimates within each cluster. CHAID and CART algorithms are applied on approximately 1000 project cost data records which were analyzed, pre-processed and used for generating fuzzy decision tree instances, followed by an evaluation method assessing prediction accuracy achieved by the classification rules produced. Even though the experimentation follows a heuristic approach, the trees built were found to fit the data properly, while the predicted effort values approximate well the actual effort.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Cyprus, 75 Kallipoleos str., CY1678, Nicosia, Cyprus

    Efi Papatheocharous & Andreas S. Andreou

Authors
  1. Efi Papatheocharous
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  2. Andreas S. Andreou
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Editor information

Editors and Affiliations

  1. Department of Systems and informatics, Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and Instituto Politécnico de Setúbal (IPS), Rua do Vale de Chaves, Estefanilha, 2910-761, Setúbal, Portugal

    Joaquim Filipe  & José Cordeiro  & 

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Papatheocharous, E., Andreou, A.S. (2009). Classification and Prediction of Software Cost through Fuzzy Decision Trees. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2009. Lecture Notes in Business Information Processing, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01347-8_20

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  • DOI: https://doi.org/10.1007/978-3-642-01347-8_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01346-1

  • Online ISBN: 978-3-642-01347-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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