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Function Point Tree-Based Function Point Analysis: Improving Reproducibility Whilst Maintaining Accuracy in Function Point Counting

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Enterprise Information Systems (ICEIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 378))

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Abstract

We propose a method to improve reproducibility whilst keeping accuracy for the Function Point Analysis (FPA) method. The proposed method is based on a new artifact model called Function Point Tree (FPT). FPT enables a standardized and systematic collection of all data required for FP counting. The new measurement method is called Function Point Tree-based Function Point Analysis (FPT-FPA). We designed FPT-FPA to comply with the IFPUG’s FPA steps. We implemented a prototype tool to show the feasibility of automation of the proposed method as well as to support its evaluation. We conducted an empirical study to evaluate FPT-FPA. Our results show general coefficients of variation lower than the maximum expected for both reproducibility and accuracy when compared to the standard FPA method.

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Notes

  1. 1.

    For the sake of simplicity, the term FPA is be used herein to refer to IFPUG’s FPA.

  2. 2.

    Reproducibility is also referred as inter-rater reliability, i.e., the degree of agreement among raters; a score of homogeneity or consensus in ratings given by different raters.

  3. 3.

    Part of Requirements Engineering-based Conceptual Modeling (REbCM)  [22].

  4. 4.

    A broader review was published before [18], aiming at any type of FPA improvement.

  5. 5.

    The latest CPM version with no major changes is from 2000.

  6. 6.

    The correct expected number of FPs achieved by the accurate FPA application.

  7. 7.

    Requirements engineering and count FPs subprocesses are not detailed in this paper.

  8. 8.

    Only 12 of 13 FPA PLs are used since the last one neither impacts the identification of the type nor contributes to the uniqueness of an elementary process.

  9. 9.

    Standard deviation (of the values measured with FPTFPA relative to the average of such measured values) divided by the average of the values measured with FPTFPA.

  10. 10.

    Standard deviation (of the values measured with FPTFPA relative to the IFPUG’s value) divided by the IFPUG’s value.

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Author information

Authors and Affiliations

  1. School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil

    Marcos de Freitas Jr., Marcelo Fantinato & Violeta Sun

  2. Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Lucinéia H. Thom

  3. Department of Electronic and Computer Engineering, Brunel University London, Uxbridge, UK

    Vanja Garaj

Authors
  1. Marcos de Freitas Jr.
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  2. Marcelo Fantinato
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  3. Violeta Sun
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  4. Lucinéia H. Thom
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  5. Vanja Garaj
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Corresponding author

Correspondence to Marcos de Freitas Jr. .

Editor information

Editors and Affiliations

  1. INSTICC and Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

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de Freitas, M., Fantinato, M., Sun, V., Thom, L.H., Garaj, V. (2020). Function Point Tree-Based Function Point Analysis: Improving Reproducibility Whilst Maintaining Accuracy in Function Point Counting. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2019. Lecture Notes in Business Information Processing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-40783-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-40783-4_10

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