Abstract
AbstractIn recent years, we have seen many performance fiascos in the deployment of new systems, such as the US health insurance web. This paper describes the functionality and architecture, as well as success stories, of a tool that helps address these types of issues. The tool allows assessing software designs regarding quality, in particular performance and reliability. Starting from a UML design with quality annotations, the tool applies model-transformation techniques to yield analyzable models. Such models are then leveraged by the tool to compute quality metrics. Finally, quality results, over the design, are presented to the engineer, in terms of the problem domain. Hence, the tool is an asset for the software engineer to evaluate system quality through software designs. While leveraging the Eclipse platform, the tool uses UML and the MARTE, DAM and DICE profiles for the system design and the quality modeling.
Funder
Horizon 2020
Ministerio de Ciencia y Tecnología
Ministerio de Ciencia e Innovacion
Universidad de Zaragoza
Publisher
Springer Science and Business Media LLC
Reference54 articles.
1. Ajmone Marsan, M., Balbo, G., Conte, G., Donatelli, S., Franceschinis, G.: Modelling with Generalized Stochastic Petri Nets. Wiley Series in Parallel Computing. John Wiley and Sons (1995)
2. Andrade, E.C., Alves, M., Matos, R., Silva, B., Maciel, P.: Openmads: An open source tool for modeling and analysis of distributed systems. In International Conference on Computer Safety, Reliability, and Security, pages 277–284. Springer, (2013)
3. Balbo, G., Silva, M. (eds.): Performance Models for Discrete Event Systems with Synchronizations: Formalisms and Analysis Techniques. Editorial KRONOS, Zaragoza, Spain (1998)
4. Becker, S., Koziolek, H., Reussner, R.: The palladio component model for model-driven performance prediction. Journal of Systems and Software 82(1), 3–22 (2009). https://doi.org/10.1016/j.jss.2008.03.066. (Special Issue: Software Performance - Modeling and Analysis.)
5. Bernardi, S., Dominguez, J.L., Gomez, A., Joubert, C., Merseguer, José, Perez-Palacin, D., Requeno, J.I., Romeu, A.: A systematic approach for performance assessment using process mining. Empirical Software Engineering, 23(6):3394–3441, 2018. https://doi.org/10.1007/s10664-018-9606-9
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