DICE

Developing Data-Intensive Applications with Iterative Quality Enhancements

PROJECT TYPE

Horizon 2020

DURATION

01.02.2015 - 31.01.2018

PROJECT MANAGER AT XLAB

Matej Artač
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644869.

The rapid increase in demand for data-intensive applications capable of exploiting Big Data technologies such as Hadoop/ MapReduce, NoSQL, cloud-based storage, and stream processing is creating massive growth opportunities for European independent software vendors (ISVs). However, developing software that meets the high-quality standards expected for business-critical cloud applications remains a barrier to this market for many small and medium ISVs, which often lack resources and expertise for advanced quality engineering.

DICE will tackle this challenge by defining a quality-driven development methodology and related tools that will markedly accelerate the development of business-critical data-intensive applications running on public or private clouds. Building on the principles of model-driven development (MDD) and on popular standards such as UML, MARTE and TOSCA, the project will first define a novel MDD methodology that can describe data and data-intensive technologies in cloud applications. A quality engineering toolchain offering simulation, verification, and numerical optimisation will leverage these extensions to drive the early design stages of the application development and guide software quality evolution.

DevOps-inspired methods for deployment, testing, continuous integration and monitoring feedback analysis will be used to accelerate the incorporation of quality in data-intensive cloud application both in public and private deployments, enhancing the capability of small and medium European ISVs to enter the Big Data market.





In 2017 XLAB became a member of OASIS, the organization for the advancement of structured information standards.

XLAB’s role

XLAB is leading the deployment and testing of data-intensive applications, especially in the early prototyping phases (WP5); continuous integration of code changes into the deployment; runtime validation of the deployed application; tools to simulate outages and faults that are expected to happen during production.