Abstract
Adapting software systems at run-time is a key issue, especially when these systems consist of components used as intermediary for human-computer interaction. In this sense, model transformation techniques have a widespread acceptance as a mechanism for adapting and evolving the software architecture of such systems. However, existing model transformations often focus on functional requirements, and quality attributes are only manually considered after the transformations are done. This paper aims to improve the quality of adaptations and evolutions in component-based software systems by taking into account quality attributes within the model transformation process. To this end, we present a quality-aware transformation process using software architecture metrics to select among many alternative model transformations. Such metrics evaluate the quality attributes of an architecture. We validate the presented quality-aware transformation process in ENIA, a geographic information system whose user interfaces are based on coarse-grained components and need to be adapted at run-time.
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Notes
- 1.
Netvibes – https://www.netvibes.com/.
- 2.
Geckoboard – https://www.geckoboard.com/.
- 3.
Cyfe – http://www.cyfe.com/.
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ACG: ENIA Poject - Development of an intelligent web agent of environmental information. http://acg.ual.es/projects/enia/
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Acknowledgments
This work was funded by the Spanish MINECO and the Andalusian Government under TIN2013-41576-R and P10-TIC-6114 projects.
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Criado, J., Martínez-Fernández, S., Ameller, D., Iribarne, L., Padilla, N. (2016). Exploring Quality-Aware Architectural Transformations at Run-Time: The ENIA Case. In: Bellatreche, L., Pastor, Ó., Almendros Jiménez, J., Aït-Ameur, Y. (eds) Model and Data Engineering. MEDI 2016. Lecture Notes in Computer Science(), vol 9893. Springer, Cham. https://doi.org/10.1007/978-3-319-45547-1_23
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