Model-Driven Approach and Implementation of Partial Model-to-Model Transformations in a CASE Tool

Author(s):  
Tomas Skersys ◽  
Saulius Pavalkis ◽  
Ingrida Lagzdinyte-Budnike
Author(s):  
Sarra Roubi ◽  
Mohammed Erramdani ◽  
Samir Mbarki

<p><span lang="EN-US">A Rich Internet Applications (RIAs) combine the simplicity of the hypertext paradigm with the flexibility of desktop interfaces. These appliations were proposed as a solution to follow the rapid growth and evolution of the Graphical User Interfaces. However, RIAs are complex applications and their development requires designing and implementation which are time-consuming and the available tools are specialized in manual design. In this paper, we present a model driven approach to generat GUI for Rich Internet Application. The approach exploits the new language IFML recently adopted by the Object Management Group. We used frameworks and technologies known to Model-Driven Engineering, such as Eclipse Modeling Framework (EMF) for Meta-modeling, Query View Transformation (QVT) for model transformations and Acceleo for code generation. The approach allows to quickly and efficiently generating a RIA focusing on the graphical aspect of the application.</span></p>


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 745
Author(s):  
Emanuel Trunzer ◽  
Birgit Vogel-Heuser ◽  
Jan-Kristof Chen ◽  
Moritz Kohnle

Data collection from distributed automated production systems is one of the main prerequisites to leverage information gain from data analysis in the context of Industrie 4.0, e.g., for the optimization of product quality. However, the realization of data collection architectures is associated with immense implementation efforts due to the heterogeneity of systems, protocols, and interfaces, as well as the multitude of involved disciplines in such projects. Therefore, this paper contributes with an approach for the model-driven generation of data collection architectures to significantly lower manual implementation efforts. Via model transformations, the corresponding source code is automatically generated from formalized models that can be created using a graphical domain-specific language. The automatically generated architecture features support for various established IIoT protocols. In a lab-scale evaluation and a unique generalized extrapolation study, the significant effort savings compared to manual programming could be quantified. In conclusion, the proposed approach can successfully mitigate the current scientific and industrial challenges to enable wide-scale access to industrial data.


Author(s):  
Sarra Roubi ◽  
Mohammed Erramdani ◽  
Samir Mbarki

<p><span lang="EN-US">A Rich Internet Applications (RIAs) combine the simplicity of the hypertext paradigm with the flexibility of desktop interfaces. These appliations were proposed as a solution to follow the rapid growth and evolution of the Graphical User Interfaces. However, RIAs are complex applications and their development requires designing and implementation which are time-consuming and the available tools are specialized in manual design. In this paper, we present a model driven approach to generat GUI for Rich Internet Application. The approach exploits the new language IFML recently adopted by the Object Management Group. We used frameworks and technologies known to Model-Driven Engineering, such as Eclipse Modeling Framework (EMF) for Meta-modeling, Query View Transformation (QVT) for model transformations and Acceleo for code generation. The approach allows to quickly and efficiently generating a RIA focusing on the graphical aspect of the application.</span></p>


2019 ◽  
pp. 293-306
Author(s):  
Sara Gotti ◽  
Samir Mbarki ◽  
Zineb Gotti ◽  
Naziha Laaz

Quite recently, considerable attention has been paid to the design, implementation and evaluation of graphical user interfaces due to the apparition of the new strategic trend of computing everywhere. Accordingly, it is necessary to adopt an abstract representation of systems front-end in order to ensure this trend. IFML (Interaction Flow Modeling Language) is a user interfaces description language used to describe the content and interaction behavior of applications front-end. It has been conceived with executability aspect that is obtained via model transformations and full code generators into functional codes. however, these code generators are often accompanied by a loss of information. The main goal of this paper is to present a new virtual machine for directly executing GUIs models designed with IFML language in combination with UML domain model; that captures the content dependency. These input models will be then run on different platforms and devices. We adopted a new model driven approach that includes the hybrid approach of interpretive compiler; through a set of transformation rules, for the implementation of the desired virtual machine.


Author(s):  
Christoph Rieger ◽  
Daniel Lucrédio ◽  
Renata Pontin M. Fortes ◽  
Herbert Kuchen ◽  
Felipe Dias ◽  
...  

2021 ◽  
Vol 11 (6) ◽  
pp. 2554
Author(s):  
Yoel Arroyo ◽  
Ana I. Molina ◽  
Miguel A. Redondo ◽  
Jesús Gallardo

This paper introduces Learn-CIAM, a new model-based methodological approach for the design of flows and for the semi-automatic generation of tools in order to support collaborative learning tasks. The main objective of this work is to help professors by establishing a series of steps for the specification of their learning courses and the obtaining of collaborative tools to support certain learning activities (in particular, for in-group editing, searching and modeling). This paper presents a complete methodological framework, how it is supported conceptually and technologically, and an application example. So to guarantee the validity of the proposal, we also present some validation processes with potential designers and users from different profiles such as Education and Computer Science. The results seem to demonstrate a positive reception and acceptance, concluding that its application would facilitate the design of learning courses and the generation of collaborative learning tools for professionals of both profiles.


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