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Performance is an important quality attribute in a software system. Software Performance Engineering comprises analysis, design, construction, measurement and validation concerning performance requirements during software development processes. Performance in software systems using message-based communication depends mostly on the Message-Oriented Middleware (MOM). Software architects need to consider MOM’s organization, configuration and usage details to get meaningful predictions about the behavior of a software system that uses such platform. When including MOM in software architecture, it is required to foresee the impact of messaging and its underlying infrastructure. Software architects may omit the MOM influence, which could lead to wrong predictions. In this article, we explore MOM’s influence through the Palladio Component Model – PCM, a component-based modeling and simulation approach. An application previously modeled with PCM was adapted to include message-oriented communication. Simulations over the model, systematic measurements, and load testing on the adapted application were performed, in order to determine how the changes in the model influenced the prediction of the application’s behavior on performance and reliability. A bottleneck that impacts performance and reliability of the original system was identified. Introducing MOM improved the system’s reliability but harmed its performance. Component-based performance simulation revealed significant differences with measurements obtained during the load testing experiments.
 I. Sommerville, Software Engineering, London: Pearson Education, 2016.
 R. H. Reussner, S. Becker, J. Happe, R. Heinrich, A. Koziolek, H. Koziolek, M. Kramer, and K. Krogmann. Modeling and Simulating Software Architectures: The Palladio Approach, Boston: The MIT Pressm 2016.
 S. Tockey, How to Engineer Software - A Model-Based Approach, New York: IEEE Computer Society & John Wiley & Sons, 2019.
 H. Koziolek, “Performance evaluation of component-based software systems: A survey,” Performance Evaluation, vol. 67 (8), pp. 634-658, 2010. https://doi.org/10.1016/j.peva.2009.07.007
 Q. Noorshams, “Modeling and Prediction of I/O Performance in Virtualized Environments,” Doctoral Thesis, Karlsruhe Institute of Technology, Karlsruhe, 2015. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000046750
 J. Happe, H. Friedrich, S. Becker, and R. H. Reussner. “A pattern-based performance completion for Message-oriented Middleware,” in Proceedings of the 7th international workshop on Software and performance (WOSP ’08), 2008, pp. 165-176. https://doi.org/10.1145/1383559.1383581
 M. Richards, R. Monson-Haefel, and D. Chappell, Java Message Service. Sebastopol, USA: O’Reilly Media, 2009.
 Z. B. Chew, “Modelling Message-oriented-middleware Brokers Using Autoregressive Models for Bottleneck Prediction,” Doctoral Thesis, University of London, London, 2013. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8832
 M Woodside, D. Petriu, and K. Siddiqui. “Performance related Completions for Software Specifications,” in Proceedings of the 24th International Conference on Software Engineering, 2002, pp. 22-32.
 Y. Liu, and I. Gorton. “Performance prediction of J2EE applications using messaging protocols,” in Proceedings of the 8th international conference on Component-Based Software Engineering (CBSE’05), 2005, pp. 1-16. https://doi.org/10.1007/11424529_1
 T.¸ Martinec, L.¸ Marek, A. Steinhauser, P. Tuma, Q. Noorshams, A. Rentschler, and R. Reussner. “Constructing performance model of JMS middleware platform,” in Proceedings of the 5th ACM/SPEC international conference on Performance engineering (ICPE ’14), 2014, pp. 123-134. https://doi.org/10.1145/2568088.2568096
 S. S. Alwakeel, and H. M. Almansour, “Modeling and Performance Evaluation of Message-oriented Middleware with Priority Queuing,” Information Technology Journal, vol. 10, pp. 61-70, 2011. https://doi.org/10.3923/itj.2011.61.70
 S. Lehrig, R. Sanders, G. Brataas, M. Cecowski, S. Ivanšek, and J. Polutnik. “CloudStore — towards scalability, elasticity, and efficiency benchmarking and analysis in Cloud computing,” Future Generation Computer Systems, vol. 38, pp. 115-126, 2018. https://doi.org/10.1016/j.future.2017.04.018
 G. Brataas, E. Stav, S. Lehrig, S. Becker, G. Kopcak, and D. Huljenic. 2013. “CloudScale: scalability management for cloud systems,” in Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering (ICPE ’13), 2013, pp. 335-338. https://doi.org/10.1145/2479871.2479920
 M. Flores González, “Modelado y simulación de funciones en la nube en plataformas Function-as-a-Service,” Master Thesis, Instituto Tecnológico de Costa Rica, Costa Rica, 2019.