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Algorithmic optimization method for effort estimation

Programming and Computer Software volume 42, pages 161–166 (2016)Cite this article

Abstract

This paper presents an improvement of an effort estimation method that can be used to predict the level of effort for software development projects. A new estimation approach based on a two-phase algorithm is used. In the first phase, we apply a calculation based on use case points (UCPs). In the second phase, we add correction values (a 1, a 2) obtained via least squares regression. This approach employs historical project data to refine the estimate. By applying the least squares regression approach, the algorithm filters out estimation errors caused by human factors and company practice.

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Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University, T.G. Masaryka 5555, Zlin, 76001, Czech Republic

    R. Silhavy, Z. Prokopova & P. Silhavy

Authors
  1. R. Silhavy
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  2. Z. Prokopova
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  3. P. Silhavy
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Corresponding author

Correspondence to R. Silhavy.

Additional information

Original Russian Text © R. Silhavy, Z. Prokopova, P. Silhavy, 2016, published in Programmirovanie, 2016, Vol. 42, No. 3.

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Silhavy, R., Prokopova, Z. & Silhavy, P. Algorithmic optimization method for effort estimation. Program Comput Soft 42, 161–166 (2016). https://doi.org/10.1134/S0361768816030087

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  • DOI: https://doi.org/10.1134/S0361768816030087

Keywords

  • Average Relative Error
  • Effort Estimation
  • Case Point
  • Software Development Project
  • Apply Informatics