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Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements

Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements

Objective

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.

Coordinator

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

Address

South Kensington Campus Exhibition Road
Sw7 2az London

United Kingdom

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 712 059

Participants (9)

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POLITECNICO DI MILANO

Italy

EU Contribution

€ 530 613,12

INSTITUTUL E-AUSTRIA TIMISOARA

Romania

EU Contribution

€ 295 375

XLAB RAZVOJ PROGRAMSKE OPREME IN SVETOVANJE DOO

Slovenia

EU Contribution

€ 356 261,88

FLEXIANT LIMITED

United Kingdom

ATHENS TECHNOLOGY CENTER ANONYMI BIOMICHANIKI EMPORIKI KAI TECHNIKI ETAIREIA EFARMOGON YPSILIS TECHNOLOGIAS

Greece

EU Contribution

€ 425 500

PRODEVELOP

Spain

EU Contribution

€ 403 100

NETFECTIVE TECHNOLOGY SA

France

EU Contribution

€ 567 875

UNIVERSIDAD DE ZARAGOZA

Spain

EU Contribution

€ 319 200

FLEXIOPS LIMITED

United Kingdom

EU Contribution

€ 344 500

Project information

Grant agreement ID: 644869

  • Start date

    1 February 2015

  • End date

    31 January 2018

Funded under:

H2020-EU.2.1.1.3.

  • Overall budget:

    € 3 954 484

  • EU contribution

    € 3 954 484

Coordinated by:

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

United Kingdom

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