Towards Uniform Management of Cloud Services by Applying Model-Driven Development

2014 ◽  
Author(s):  
Toni Mastelic ◽  
Ivona Brandic ◽  
Andres Garcia Garcia
Keyword(s):  
Cloud Services ◽  
Model Driven Development ◽  
Model Driven

Towards uniform management of multi-layered cloud services by applying model-driven development

2016 ◽  
Vol 121 ◽  
pp. 358-371 ◽  
Author(s):  
Toni Mastelić ◽  
Andrés García García ◽  
Ivona Brandić
Keyword(s):  
Cloud Services ◽  
Model Driven Development ◽  
Model Driven

Model-driven development of composite context-aware web applications

2009 ◽  
Vol 51 (8) ◽  
pp. 1244-1260 ◽  
Author(s):  
Georgia M. Kapitsaki ◽  
Dimitrios A. Kateros ◽  
George N. Prezerakos ◽  
Iakovos S. Venieris
Keyword(s):  
Web Applications ◽  
Context Aware ◽  
Model Driven Development ◽  
Model Driven

scholarly journals Model-driven development platform selection: four industry case studies

2021 ◽  
Author(s):  
Siamak Farshidi ◽  
Slinger Jansen ◽  
Sven Fortuin
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Decision Makers ◽  
Development Activity ◽  
Model Driven Development ◽  
Domain Experts ◽  
Theoretical Contribution ◽  
Model Driven ◽  
Development Platform ◽  
Software Production

AbstractModel-driven development platforms shift the focus of software development activity from coding to modeling for enterprises. A significant number of such platforms are available in the market. Selecting the best fitting platform is challenging, as domain experts are not typically model-driven deployment platform experts and have limited time for acquiring the needed knowledge. We model the problem as a multi-criteria decision-making problem and capture knowledge systematically about the features and qualities of 30 alternative platforms. Through four industry case studies, we confirm that the model supports decision-makers with the selection problem by reducing the time and cost of the decision-making process and by providing a richer list of options than the enterprises considered initially. We show that having decision knowledge readily available supports decision-makers in making more rational, efficient, and effective decisions. The study’s theoretical contribution is the observation that the decision framework provides a reliable approach for creating decision models in software production.

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