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Calibrating function complexity in enhancement project for improving function points analysis estimation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63537918" target="_blank" >RIV/70883521:28140/21:63537918 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007%2F978-3-030-90318-3_67" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-90318-3_67</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-90318-3_67" target="_blank" >10.1007/978-3-030-90318-3_67</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Calibrating function complexity in enhancement project for improving function points analysis estimation

  • Original language description

    Producing a good software product on time and within budget, the initial software estimation takes a significant role. Reality has shown that most software fails because the initial software estimation is not correct. Many researchers have proposed methods for software estimation. It has been developed since the 70s of the last century, but it is still of great interest until now. We also know that creating a new software product is difficult; it is even more difficult to innovate. In the framework of this paper, we propose an improved method based on the FPA method of IFPUG. We named this proposed model is Calibrating Function Complexity in Enhancement Project (CFCEP). This method is based on the Linear Regression technique to give coefficients of function complexity. The experimental results based on the ISBSG dataset show that the estimation based on this new coefficient gives much better results than using the coefficients of the standard FPA method. © 2021, 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

    2021

  • 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

    978-303090317-6

  • ISSN

    23673370

  • e-ISSN

    2367-3389

  • Number of pages

    13

  • Pages from-to

    857-869

  • Publisher name

    Springer Science and Business Media Deutschland GmbH

  • Place of publication

    Berlín

  • Event location

    Vsetín

  • Event date

    Oct 1, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article