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An Approach to Adjust Effort Estimation of Function Point Analysis

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Book cover Software Engineering and Algorithms (CSOC 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 230))

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Abstract

This study presents a modified approach to adjust a software development effort estimation. The AdamOptimizer-based regression model is adopted to adjust and enhance the accuracy of effort estimation. This approach is derived into three phases. The first step deals with the logarithmized formula of effort estimation computed by Function Point Analysis and Productivity Delivery Rate. The Adam-Optimizer-based regression model is examined in the second phase, and the ISBSG repository 2020 release R1 is considered as a historical dataset in this paper. Moreover, the K-Fold cross-validation technique is adopted to tunning the training model. In the following phase, all results are evaluated by statistical significance and the goodness of fit measure. Finally, a proposed approach is compared with others: Capers Jones, and the Mean Effort.

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Acknowledgment

This work was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlín, under Project IGA/CebiaTech/2021/001.

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Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 76001, Zlin, Czech Republic

    Huynh Thai Hoc, Vo Van Hai & Ho Le Thi Kim Nhung

Authors
  1. Huynh Thai Hoc
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  2. Vo Van Hai
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  3. Ho Le Thi Kim Nhung
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Corresponding author

Correspondence to Huynh Thai Hoc .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Hoc, H.T., Van Hai, V., Nhung, H.L.T.K. (2021). An Approach to Adjust Effort Estimation of Function Point Analysis. In: Silhavy, R. (eds) Software Engineering and Algorithms. CSOC 2021. Lecture Notes in Networks and Systems, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-030-77442-4_45

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