Early Size and Effort Estimation of Mobile Application Development

With the increased complexity in mobile applications, many challenges and issues emerged for the software project management team to develop mobile application effectively and accurately. Effort estimation is one of the most critical issues the Software management pro...

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Autores principales:	Ziema Mushtaq, Sami Alshmrany, Fahad Alturise, Tamim Alkhalifah
Formato:	article
Lenguaje:	EN
Publicado:	European Alliance for Innovation (EAI) 2022
Materias:	effort estimation mobile application development mobile effort estimation methodology hybrid machine learning techniques cpeem approaches Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/6ee02a7c789e4ae5badd2db17f23b66b
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spelling	oai:doaj.org-article:6ee02a7c789e4ae5badd2db17f23b66b2021-11-30T11:07:32ZEarly Size and Effort Estimation of Mobile Application Development2032-944X10.4108/eai.31-5-2021.170010https://doaj.org/article/6ee02a7c789e4ae5badd2db17f23b66b2022-01-01T00:00:00Zhttps://eudl.eu/pdf/10.4108/eai.31-5-2021.170010https://doaj.org/toc/2032-944XWith the increased complexity in mobile applications, many challenges and issues emerged for the software project management team to develop mobile application effectively and accurately. Effort estimation is one of the most critical issues the Software management project team faces in general, and the mobile application development team in specific. Effort estimation helps to approximate the cost required for successful software application development. The mobile application is distinct in various aspects from the traditional software and web-based applications. There is a need for a specific methodology to be followed for accurate estimation of size and efforts. This research aims to review the effectiveness of COSMIC and Machine Learning techniques in performing mobile effort estimation and propose a hybrid approach for efficient mobile effort estimation. This research work's mains represent the methodology followed to achieve the input parameters and mobile applications' efforts using a tailor-made approach. The significance of this research work is to propose a framework that will help both researchers and mobile application estimators approximate the efficient efforts precisely.Ziema MushtaqSami AlshmranyFahad AlturiseTamim AlkhalifahEuropean Alliance for Innovation (EAI)articleeffort estimation mobile application development mobile effort estimation methodologyhybrid machine learning techniquescpeem approachesScienceQMathematicsQA1-939Electronic computers. Computer scienceQA75.5-76.95ENEAI Endorsed Transactions on Energy Web, Vol 9, Iss 37 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	effort estimation mobile application development mobile effort estimation methodology hybrid machine learning techniques cpeem approaches Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
spellingShingle	effort estimation mobile application development mobile effort estimation methodology hybrid machine learning techniques cpeem approaches Science Q Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95 Ziema Mushtaq Sami Alshmrany Fahad Alturise Tamim Alkhalifah Early Size and Effort Estimation of Mobile Application Development
description	With the increased complexity in mobile applications, many challenges and issues emerged for the software project management team to develop mobile application effectively and accurately. Effort estimation is one of the most critical issues the Software management project team faces in general, and the mobile application development team in specific. Effort estimation helps to approximate the cost required for successful software application development. The mobile application is distinct in various aspects from the traditional software and web-based applications. There is a need for a specific methodology to be followed for accurate estimation of size and efforts. This research aims to review the effectiveness of COSMIC and Machine Learning techniques in performing mobile effort estimation and propose a hybrid approach for efficient mobile effort estimation. This research work's mains represent the methodology followed to achieve the input parameters and mobile applications' efforts using a tailor-made approach. The significance of this research work is to propose a framework that will help both researchers and mobile application estimators approximate the efficient efforts precisely.
format	article
author	Ziema Mushtaq Sami Alshmrany Fahad Alturise Tamim Alkhalifah
author_facet	Ziema Mushtaq Sami Alshmrany Fahad Alturise Tamim Alkhalifah
author_sort	Ziema Mushtaq
title	Early Size and Effort Estimation of Mobile Application Development
title_short	Early Size and Effort Estimation of Mobile Application Development
title_full	Early Size and Effort Estimation of Mobile Application Development
title_fullStr	Early Size and Effort Estimation of Mobile Application Development
title_full_unstemmed	Early Size and Effort Estimation of Mobile Application Development
title_sort	early size and effort estimation of mobile application development
publisher	European Alliance for Innovation (EAI)
publishDate	2022
url	https://doaj.org/article/6ee02a7c789e4ae5badd2db17f23b66b
work_keys_str_mv	AT ziemamushtaq earlysizeandeffortestimationofmobileapplicationdevelopment AT samialshmrany earlysizeandeffortestimationofmobileapplicationdevelopment AT fahadalturise earlysizeandeffortestimationofmobileapplicationdevelopment AT tamimalkhalifah earlysizeandeffortestimationofmobileapplicationdevelopment
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Early Size and Effort Estimation of Mobile Application Development

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