Comparative analysis of UCP and SLIM methods to estimate the development of software products

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference on IT in Business and Industry, ITBI 2021

Год издания: 2021

Идентификатор DOI: 10.1088/1742-6596/2032/1/012121

Аннотация: This study is devoted to analysis different methods to estimate the software products development. The following most popular methods were selected for the study: Use Case Points and SLIM. The considered methods are algorithmic and are used in case of insufficient experience of the project team to use empirical calculation methods.Показать полностьюA comparative analysis of these methods was also carried out based on calculating the forecasting error for IT projects for various platforms, such as a mobile device and a personal computer. The disadvantages of using the considered methods for developing applications for mobile platforms were identified. Based on the research results, it was concluded that today algorithmic methods for assessing labor intensity cannot give the best results and must be changed to adapt them to mobile software, considering its specific specifics, which makes it advisable to continue researching this industry in direction of mobile development. © 2021 Institute of Physics Publishing. All rights reserved.

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Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 2032, Is. 1

Номера страниц: 12121

ISSN журнала: 17426588

Издатель: IOP Publishing Ltd

Персоны

  • Markevich E.A. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)
  • Kukartsev V.V. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation, Reshetnev Siberian State University of Science and Technology, 31, Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Strokan A.I. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)
  • Nozdrenko E.A. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)
  • Lysyannikova N.N. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)
  • Mongush S.Ch. (Tuva State University, 36, Lenin st., Kyzyl, 667000, Russian Federation)

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