Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements

DICE was a collaborative research project which received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644869. The purpose of the project was to define a development methodology and related tools to accelerate the development of business-critical data-intensive cloud applications.

Building on the principles of model-driven development (MDD) and on popular standards such as UML, MARTE and TOSCA, the project created a methodology to define data and data-intensive technologies in cloud applications. The consortium applied the methodology to develop a quality engineering toolchain offering simulation, verification, and numerical optimization to drive early design stages of application development and guide software quality evolution.

The DICE consortium, coordinated by Imperial College (UK) included Athens Technology Center (Greece), ProDevelop (Spain), Netfective (France), Flexiant (UK), University of Zaragoza (Spain), Xlab Razvoj (Slovenia), Institutul E-AUS (Romania) and Politecnico di Milano (Italy).

Serving as an end-user of DICE, ATC contributed in developing software that meets the high-quality standards expected for business-critical cloud applications, guided by the consortium’s expertise in advanced quality engineering. ATC’s software engineers and architects with knowledge in UML modeling enhanced DICE tools and exploited Big Data technologies such as Hadoop/MapReduce, NoSQL, cloud-based storage, and stream processing. The ultimate goal for ATC was to make a fundamental step towards entering the Big Data market.

The project started in February 2015 and had a duration of 36 months.

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