Modelos segmentados de estimación del esfuerzo de desarrollo del SoftwareUn caso de estudio con la base de datos ISBSG

  1. J. Cuadrado Gallego 1
  2. Daniel Rodríguez 2
  3. Miguel Ángel Sicilia 3
  1. 1 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

  2. 2 University of Reading
    info

    University of Reading

    Reading, Reino Unido

    ROR https://ror.org/05v62cm79

  3. 3 Universidad de Alcalá
    info

    Universidad de Alcalá

    Alcalá de Henares, España

    ROR https://ror.org/04pmn0e78

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Journal:
Revista de procesos y métricas de las tecnologías de la información

ISSN: 1886-4554

Year of publication: 2004

Volume: 1

Issue: 2

Pages: 25-30

Type: Article

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Sustainable development goals

Abstract

Parametric sofware effort estimation models use historical project databases to adjust the parameters of the required effort function. The use of databases with data coming from heterogeneous sources often entail that the resulting models are subject to excessively high mean errors, due to the fact that data are widely diverging in magnitude. In order to improve this situation, the segmentation of the input domain has been proposed, so that a regression model with different parameters is obtained for each segment. In this paper, the use of well-known clustering algorithms in a recursive way is described as a technique to obtain segmented models of the kind mentioned. Concretely, the ISBSG database and the EM algorithm are use as a demonstration of the results that can be obtained through that technique.

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