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.

Fields of science

• natural sciencescomputer and information sciencesdata sciencebig data
• natural sciencescomputer and information sciencessoftwaresoftware applicationssystem software
• social scienceseconomics and businesseconomicsproduction economicsproductivity
• social sciencessociologygovernancetaxation
• natural sciencescomputer and information sciencesdatabasesnon-relational databases

Keywords

• Quality
• reliability
• efficiency
• safety
• Big data
• Cloud computing
• UML
• MARTE
• TOSCA

Programme(s)

• H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) Main Programme
• H2020-EU.2.1.1.3. - Future Internet: Software, hardware, Infrastructures, technologies and services

Topic(s)

• ICT-09-2014 - Tools and Methods for Software Development

Funding Scheme

Coordinator

Participants (9)