DICE: Quality-driven development of data-intensive cloud applications

G. Casale, D. Ardagna, M. Artac, F. Barbier, E. Di Nitto, A. Henry, G. Iuhasz, C. Joubert, J. Merseguer, V. I. Munteanu, J. F. Pérez, D. Petcu, M. Rossi, C. Sheridan, I. Spais, D. Vladušič

Research output: Chapter in Book/ReportConference contribution

54 Scopus citations


Model-driven engineering (MDE) often features quality assurance (QA) techniques to help developers creating software that meets reliability, efficiency, and safety requirements. In this paper, we consider the question of how quality-aware MDE should support data-intensive software systems. This is a difficult challenge, since existing models and QA techniques largely ignore properties of data such as volumes, velocities, or data location. Furthermore, QA requires the ability to characterize the behavior of technologies such as Hadoop/MapReduce, NoSQL, and stream-based processing, which are poorly understood from a modeling standpoint. To foster a community response to these challenges, we present the research agenda of DICE, a quality-aware MDE methodology for data-intensive cloud applications. DICE aims at developing a quality engineering tool chain offering simulation, verification, and architectural optimization for Big Data applications. We overview some key challenges involved in developing these tools and the underpinning models.

Translated title of the contributionDICE: Desarrollo basado en la calidad de aplicaciones de nube con uso intensivo de datos
Original languageEnglish (US)
Title of host publicationProceedings - 7th International Workshop on Modeling in Software Engineering, MiSE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781479919345
StatePublished - Jan 1 2015
Externally publishedYes
Event7th International Workshop on Modeling in Software Engineering, MiSE 2015 - Florence, Italy
Duration: May 16 2015May 17 2015


Conference7th International Workshop on Modeling in Software Engineering, MiSE 2015

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Software


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