The rapid increase in demand for data-intensive Big Data applications calls for a new generation of software engineering methods. In particular, meeting quality goals for business-critical data-intensive applications that run on the cloud is a complex challenge. DICE will define a quality-driven development methodology to accelerate the implementation and testing of data-intensive cloud applications. Building on the principles of model-driven development (MDD), the DICE research vision intends to define a novel MDD methodology to design and evaluate the quality properties of data and Big Data technologies in cloud applications. A quality engineering tool chain offering simulation, verification, and numerical optimization will use these extensions to drive the early design of the application and guide the evolution of its quality characteristics. DevOps-inspired methods for deployment, testing, continuous integration and monitoring feedback analysis will be adopted to accelerate the incorporation of quality in data-intensive cloud applications
