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A productivity optimising model for improving software effort estimation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F20%3A63526961" target="_blank" >RIV/70883521:28140/20:63526961 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-030-63322-6_62" target="_blank" >http://dx.doi.org/10.1007/978-3-030-63322-6_62</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-63322-6_62" target="_blank" >10.1007/978-3-030-63322-6_62</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A productivity optimising model for improving software effort estimation

  • Original language description

    The estimation of software development effort is a critical task for the effective management of any software industry. Despite the fact that it has been under development for a long time - along with many contributions from many authors seeking to improve the accuracy of software effort estimation, it is still of great interest to many researchers. This study proposed an improved effort estimation model, named the Productivity Optimising Model. This model was designed, based on the Function Points Measurement method and the Multiple Linear Regression model. The Multiple Linear Regression model was built based on the research of historical datasets in order to provide an estimation model so that one can determine the optimising productivity, and then it is easy to calculate the effort. The effort result of this model was compared to the others that were calculated by the Mean Value of Productivity of the tested dataset, and the Capers Jones method. It proved that proposed method gives better accuracy results than the other models. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Advances in Intelligent Systems and Computing Volume 1294

  • ISBN

    978-303063321-9

  • ISSN

    21945357

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    735-746

  • Publisher name

    Springer Science and Business Media Deutschland GmbH

  • Place of publication

    Berlín

  • Event location

    Vsetín

  • Event date

    Oct 14, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article