ArticleAutomated software engineering2022
HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications.
Article in Automated software engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Model-Driven Engineering Techniques and Tools for Machine Learning-Enabled IoT Applications: A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
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3 authors.
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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.
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