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Improving the COSMIC Approximate Sizing Using the Fuzzy Logic EPCU Model

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Software Measurement (Mensura 2015, IWSM 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 230))

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Abstract

In software engineering, the standards for functional size measurement require, for accurate measurement results, that the functionality to be measured be fully known. Therefore, in the early phases of software development when there is a lack of details, approximate sizing approaches must be used instead of the standards themselves: such approximate sizing techniques are typically based on the analysis of historical data of the functional size of a number of completed projects within an organization. This paper revisits a fuzzy logic size approximation technique – the EPCU model, and presents an improved version, which lifts a number of constraints on its design, considering the Vogelezang dataset used in the literature to define the Equal Size Bands approximation approach.

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Notes

  1. 1.

    Mean Magnitude of Relative Error (MMRE).

  2. 2.

    Standard Deviation of MRE (SDMRE).

  3. 3.

    ALFA project was a project from a Mexican Federal Institution, for confidentiality purposes the Use Cases was are referred by sequential numbers only.

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Author information

Authors and Affiliations

  1. École de technologie supérieure – Université du Québec, Montréal, Canada

    Francisco Valdés Souto & Alain Abran

Authors
  1. Francisco Valdés Souto
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  2. Alain Abran
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Corresponding author

Correspondence to Francisco Valdés Souto .

Editor information

Editors and Affiliations

  1. Institute of Information Systems and Digital Economy, Warsaw School of Economics, Warsaw, Poland

    Andrzej Kobyliński

  2. Institute of Information Systems and Digital Economy, Warsaw School of Economics, Warsaw, Poland

    Beata Czarnacka-Chrobot

  3. Polish Software Measurement Association, Warsaw, Poland

    Jaroslaw Świerczek

Appendix A: The Full Data Set of the Information Collected in This Case Study

Appendix A: The Full Data Set of the Information Collected in This Case Study

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Souto, F.V., Abran, A. (2015). Improving the COSMIC Approximate Sizing Using the Fuzzy Logic EPCU Model. In: Kobyliński, A., Czarnacka-Chrobot, B., Świerczek, J. (eds) Software Measurement. Mensura IWSM 2015 2015. Lecture Notes in Business Information Processing, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-319-24285-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-24285-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24284-2

  • Online ISBN: 978-3-319-24285-9

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