Your browser doesn't support javascript.
loading
HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications.
Mehrabi, Maryam; Zamani, Bahman; Hamou-Lhadj, Abdelwahab.
Afiliação
  • Mehrabi M; MDSE Research Group, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran.
  • Zamani B; MDSE Research Group, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran.
  • Hamou-Lhadj A; Department of Electrical and Computer Engineering, Concordia University, Montreal, QC Canada.
Autom Softw Eng ; 29(2): 56, 2022.
Article em En | MEDLINE | ID: mdl-36185751
ABSTRACT
The development of IoT-based Android health monitoring mobile applications (apps) using traditional software development methods is a challenging task. Developers need to be familiar with various programming languages to manage the heterogeneity of hardware and software systems and to support different communication technologies. To address these problems, in this paper, we first analyze the domain of health monitoring mobile applications and then propose a framework based on model-driven engineering that accelerates the development of such systems. The proposed framework, called HealMA, includes a domain-specific modeling language, a graphical modeling editor, several validation rules, and a set of model-to-code transformations, all packed as an Eclipse plugin. We evaluated the framework to assess its applicability in generating various mobile health applications, as well as its impact on software productivity. To this end, four different health monitoring applications have been automatically generated. Then, we evaluated the productivity of software developers by comparing the time and effort it takes to use HealMA compared to a code-centric process. As part of the evaluation, we also evaluated the usability of HealMA-generated apps by conducting a user study. The results show that HealMA is both applicable and beneficial for automatic generation of usable IoT-based Android health monitoring apps.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article