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

doi:10.1109/MiSE.2015.21

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

Título traducido de la contribución: DICE: Desarrollo basado en la calidad de aplicaciones de nube con uso intensivo de datos

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

Producción científica: Capítulo en Libro/Reporte › Contribución a la conferencia

54 Citas (Scopus)

Resumen

La ingeniería basada en modelos (MDE) a menudo incluye técnicas de garantía de calidad (QA) para ayudar a los desarrolladores a crear software que cumpla con los requisitos de confiabilidad, eficiencia y seguridad. En este documento, consideramos la cuestión de cómo MDE, consciente de la calidad, debería apoyar los sistemas de software que requieren una gran cantidad de datos. Este es un reto difícil, ya que los modelos y las técnicas de garantía de calidad existentes ignoran en gran medida las propiedades de los datos, como los volúmenes, las velocidades o la ubicación de los datos. Además, la garantía de calidad requiere la capacidad de caracterizar el comportamiento de tecnologías como Hadoop/MapReduce, NoSQL y el procesamiento basado en secuencias, que no se comprenden bien desde el punto de vista del modelado. Para fomentar una respuesta comunitaria a estos desafíos, presentamos la agenda de investigación de DICE, una metodología MDE de calidad para aplicaciones de cloud intensivas en datos. El objetivo de DICE es desarrollar una cadena de herramientas de ingeniería de calidad que ofrezca simulación, verificación y optimización arquitectónica para aplicaciones Big Data. Resumimos algunos de los principales desafíos que implica el desarrollo de estas herramientas y de los modelos que las sustentan.

Título traducido de la contribución	DICE: Desarrollo basado en la calidad de aplicaciones de nube con uso intensivo de datos
Idioma original	Inglés estadounidense
Título de la publicación alojada	Proceedings - 7th International Workshop on Modeling in Software Engineering, MiSE 2015
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	78-83
Número de páginas	6
ISBN (versión digital)	9781479919345
DOI	https://doi.org/10.1109/MiSE.2015.21
Estado	Publicada - ene. 1 2015
Publicado de forma externa	Sí
Evento	7th International Workshop on Modeling in Software Engineering, MiSE 2015 - Florence, Italia Duración: may. 16 2015 → may. 17 2015

Conferencia

Conferencia	7th International Workshop on Modeling in Software Engineering, MiSE 2015
País/Territorio	Italia
Ciudad	Florence
Período	5/16/15 → 5/17/15

Áreas temáticas de ASJC Scopus

Modelización y simulación
Software

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10.1109/MiSE.2015.21

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Casale, G., Ardagna, D., Artac, M., Barbier, F., Di Nitto, E., Henry, A., Iuhasz, G., Joubert, C., Merseguer, J., Munteanu, V. I., Pérez, J. F., Petcu, D., Rossi, M., Sheridan, C., Spais, I., & Vladušič, D. (2015). DICE: Quality-driven development of data-intensive cloud applications. En Proceedings - 7th International Workshop on Modeling in Software Engineering, MiSE 2015 (pp. 78-83). Artículo 7167407 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MiSE.2015.21

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title = "DICE: Quality-driven development of data-intensive cloud applications",

abstract = "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.",

author = "G. Casale and D. Ardagna and M. Artac and F. Barbier and {Di Nitto}, E. and A. Henry and G. Iuhasz and C. Joubert and J. Merseguer and Munteanu, {V. I.} and P{\'e}rez, {J. F.} and D. Petcu and M. Rossi and C. Sheridan and I. Spais and D. Vladu{\v s}i{\v c}",

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Casale, G, Ardagna, D, Artac, M, Barbier, F, Di Nitto, E, Henry, A, Iuhasz, G, Joubert, C, Merseguer, J, Munteanu, VI, Pérez, JF, Petcu, D, Rossi, M, Sheridan, C, Spais, I & Vladušič, D 2015, DICE: Quality-driven development of data-intensive cloud applications. En Proceedings - 7th International Workshop on Modeling in Software Engineering, MiSE 2015., 7167407, Institute of Electrical and Electronics Engineers Inc., pp. 78-83, 7th International Workshop on Modeling in Software Engineering, MiSE 2015, Florence, Italia, 5/16/15. https://doi.org/10.1109/MiSE.2015.21

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AU - Merseguer, J.

AU - Munteanu, V. I.

AU - Pérez, J. F.

AU - Petcu, D.

AU - Rossi, M.

AU - Sheridan, C.

AU - Spais, I.

AU - Vladušič, D.

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

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Conferencia

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