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Towards a correction factors-based software productivity using ensemble approach for early software development effort estimation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63555918" target="_blank" >RIV/70883521:28140/22:63555918 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-031-09070-7_35" target="_blank" >http://dx.doi.org/10.1007/978-3-031-09070-7_35</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-09070-7_35" target="_blank" >10.1007/978-3-031-09070-7_35</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards a correction factors-based software productivity using ensemble approach for early software development effort estimation

  • Original language description

    Accuracy of effort estimation is one of the necessary conditions for efficiently managing software development projects. Since the information available in the early stages of software development is insufficient, software sizing metrics are considered critical factors for effort estimation. However, there is no consistent method for converting software sizing into the corresponding effort. Previous estimation methods have not considered software productivity a critical factor in estimating effort based on software sizing. This paper proposes a software productivity model based on correction factors in the Optimizing Correction Factors method through an ensemble construction mechanism of three popular machine learning techniques. The results show that using the proposed software productivity minimizes the estimation error of the methods compared to using fixed productivity metrics. © 2022, 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

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Lecture Notes in Networks and Systems

  • ISBN

    978-3-031-09069-1

  • ISSN

    2367-3370

  • e-ISSN

    2367-3389

  • Number of pages

    13

  • Pages from-to

    413-425

  • Publisher name

    Springer International Publishing AG

  • Place of publication

    Basel

  • Event location

    on-line

  • Event date

    Apr 26, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000893645700035