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ALBA: a model-driven framework for the automatic generation of android location-based apps
In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more effective tools and techniques to generate the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818077/ http://dx.doi.org/10.1007/s10515-020-00278-3 |
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author | Gharaat, Mohammadali Sharbaf, Mohammadreza Zamani, Bahman Hamou-Lhadj, Abdelwahab |
author_facet | Gharaat, Mohammadali Sharbaf, Mohammadreza Zamani, Bahman Hamou-Lhadj, Abdelwahab |
author_sort | Gharaat, Mohammadali |
collection | PubMed |
description | In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more effective tools and techniques to generate these apps. Many of these apps are location-based apps in which users receive services based on their geographical location. In this paper, we propose a model-driven approach for the automatic generation of Android location-based mobile apps. Our framework, called ALBA, consists of a domain-specific modeling language, a modeling tool, and a plugin which includes model to code transformations. The modeling tool enables a novice designer to model a location-based app. The model is validated against the predefined constraints and the editor prevents creating invalid models. The designer uses the plugin to generate the Android code of the app. The evaluation of our work is two fold. First, to evaluate the generalizability of the ALBA framework, we conducted an experiment which includes the generation of four industrial location-based apps. Second, to evaluate the usability and quality of both the framework and the generated apps, we conducted a case study consists of three experiments. The results of the evaluation are promising both in terms of the applicability of the framework and the quality of the generated apps. |
format | Online Article Text |
id | pubmed-7818077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-78180772021-01-21 ALBA: a model-driven framework for the automatic generation of android location-based apps Gharaat, Mohammadali Sharbaf, Mohammadreza Zamani, Bahman Hamou-Lhadj, Abdelwahab Autom Softw Eng Article In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more effective tools and techniques to generate these apps. Many of these apps are location-based apps in which users receive services based on their geographical location. In this paper, we propose a model-driven approach for the automatic generation of Android location-based mobile apps. Our framework, called ALBA, consists of a domain-specific modeling language, a modeling tool, and a plugin which includes model to code transformations. The modeling tool enables a novice designer to model a location-based app. The model is validated against the predefined constraints and the editor prevents creating invalid models. The designer uses the plugin to generate the Android code of the app. The evaluation of our work is two fold. First, to evaluate the generalizability of the ALBA framework, we conducted an experiment which includes the generation of four industrial location-based apps. Second, to evaluate the usability and quality of both the framework and the generated apps, we conducted a case study consists of three experiments. The results of the evaluation are promising both in terms of the applicability of the framework and the quality of the generated apps. Springer US 2021-01-21 2021 /pmc/articles/PMC7818077/ http://dx.doi.org/10.1007/s10515-020-00278-3 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Gharaat, Mohammadali Sharbaf, Mohammadreza Zamani, Bahman Hamou-Lhadj, Abdelwahab ALBA: a model-driven framework for the automatic generation of android location-based apps |
title | ALBA: a model-driven framework for the automatic generation of android location-based apps |
title_full | ALBA: a model-driven framework for the automatic generation of android location-based apps |
title_fullStr | ALBA: a model-driven framework for the automatic generation of android location-based apps |
title_full_unstemmed | ALBA: a model-driven framework for the automatic generation of android location-based apps |
title_short | ALBA: a model-driven framework for the automatic generation of android location-based apps |
title_sort | alba: a model-driven framework for the automatic generation of android location-based apps |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818077/ http://dx.doi.org/10.1007/s10515-020-00278-3 |
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