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Decision Framework for Cross-Platform Mobile Development Frameworks Using an Integrated Multi-Criteria Decision-Making Methodology

Decision Framework for Cross-Platform Mobile Development Frameworks Using an Integrated Multi-Criteria Decision-Making Methodology

Mohamed Lachgar, Mohamed Hanine, Hanane Benouda, Younes Ommane
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 22
ISSN: 1937-9412|EISSN: 1937-9404|EISBN13: 9781683180449|DOI: 10.4018/IJMCMC.297928
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MLA

Lachgar, Mohamed, et al. "Decision Framework for Cross-Platform Mobile Development Frameworks Using an Integrated Multi-Criteria Decision-Making Methodology." IJMCMC vol.13, no.1 2022: pp.1-22. http://doi.org/10.4018/IJMCMC.297928

APA

Lachgar, M., Hanine, M., Benouda, H., & Ommane, Y. (2022). Decision Framework for Cross-Platform Mobile Development Frameworks Using an Integrated Multi-Criteria Decision-Making Methodology. International Journal of Mobile Computing and Multimedia Communications (IJMCMC), 13(1), 1-22. http://doi.org/10.4018/IJMCMC.297928

Chicago

Lachgar, Mohamed, et al. "Decision Framework for Cross-Platform Mobile Development Frameworks Using an Integrated Multi-Criteria Decision-Making Methodology," International Journal of Mobile Computing and Multimedia Communications (IJMCMC) 13, no.1: 1-22. http://doi.org/10.4018/IJMCMC.297928

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Abstract

Because of the growing popularity of smartphones and tablets, the use of mobile applications has exploded recently. However, the variety of mobile platforms compels developers to create an app for each, making the process more complex and expensive. Thus, open-source cross-platform mobile frameworks have been developed to address this problem, allowing the same code to be imported across various operating systems. This paper comes to propose a new framework for the selection of the appropriate platform for the implementation of a cross-platform mobile application. This framework is based on the most used multi-criteria decision-making (MCDM) methods, namely analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) methods are used. A demonstrative example is proposed to illustrate the suggested methodology.