Estimación de variables en proyectos de desarrollo de software (PDS)

  1. Javier Aroba Páez 1
  2. Isabel Ramos Román 2
  3. Jose C. Riquelme Santos 2
  1. 1 Universidad de Huelva
    info

    Universidad de Huelva

    Huelva, España

    ROR https://ror.org/03a1kt624

  2. 2 Universidad de Sevilla
    info

    Universidad de Sevilla

    Sevilla, España

    ROR https://ror.org/03yxnpp24

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

ISSN: 1886-4554

Year of publication: 2004

Volume: 1

Issue: 2

Pages: 3-12

Type: Article

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Abstract

The application of some Data Mining techniques to Software Development Projects (SDP) numeric databa-ses (obtained through the simulation), facilitates the obtaining of qualitative information about the project evolution. Many of these techniques are descriptive, like the clustering, for which reason we don't have the capacity, a priori, to forecast results (project variables) from a new data set (project attributes) of a SDP. In this paper we try some statistic methods to forecast these variables from a new set of values of the attributes, so that the obtained results can be compared. The goal is to check if the project variables can be forecasted without having to simulate the whole project, and with low margin of error.

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