Mehrabi Maryam, Zamani Bahman, Hamou-Lhadj Abdelwahab
MDSE Research Group, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran.
Department of Electrical and Computer Engineering, Concordia University, Montreal, QC Canada.
Autom Softw Eng. 2022;29(2):56. doi: 10.1007/s10515-022-00363-9. Epub 2022 Sep 27.
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.
使用传统软件开发方法开发基于物联网的安卓健康监测移动应用程序是一项具有挑战性的任务。开发人员需要熟悉各种编程语言，以管理硬件和软件系统的异构性，并支持不同的通信技术。为了解决这些问题，在本文中，我们首先分析了健康监测移动应用程序的领域，然后提出了一个基于模型驱动工程的框架，该框架可加速此类系统的开发。所提出的框架名为HealMA，包括一种特定领域的建模语言、一个图形建模编辑器、若干验证规则以及一组模型到代码的转换，所有这些都打包为一个Eclipse插件。我们对该框架进行了评估，以评估其在生成各种移动健康应用程序方面的适用性，以及对软件生产率的影响。为此，已经自动生成了四个不同的健康监测应用程序。然后，我们通过比较使用HealMA与以代码为中心的过程所需的时间和精力，评估了软件开发人员的生产率。作为评估的一部分，我们还通过进行用户研究评估了HealMA生成的应用程序的可用性。结果表明，HealMA对于自动生成可用的基于物联网的安卓健康监测应用程序既适用又有益。
