57744 20190709135419.0 doi 10.1007/s10515-015-0186-2 sideral 93774 ART-2017-93774 eng (orcid)0000-0001-7982-0359 Rodríguez, Ricardo J. Universidad de Zaragoza A Petri Net Tool for Software Performance Estimation Based on Upper Throughput Bounds 2017 Access copy available to the general public Unrestricted Functional and non-functional properties analysis (i.e., dependability, security, or performance) ensures that requirements are fulfilled during the design phase of software systems. However, the Unified Modelling Language (UML), standard de facto in industry for software systems modelling, is unsuitable for any kind of analysis but can be tailored for specific analysis purposes through profiling. For instance, the MARTE profile enables to annotate performance data within UML models that can be later transformed to formal models (e.g., Petri nets or Timed Automatas) for performance evaluation. A performance (or throughput) estimation in such models normally relies on a whole exploration of the state space, which becomes unfeasible for large systems. To overcome this issue upper throughput bounds are computed, which provide an approximation to the real system throughput with a good complexity-accuracy trade-off. This paper introduces a tool, named PeabraiN, that estimates the performance of software systems via their UML models. To do so, UML models are transformed to Petri nets where performance is estimated based on upper throughput bounds computation. PeabraiN also allows to compute other features on Petri nets, such as the computation of upper and lower marking place bounds, and to simulate using an approximate (continuous) method. We show the applicability of PeabraiN by evaluating the performance of a building closed circuit TV system. info:eu-repo/grantAgreement/ES/MICINN/TIN2014-58457-R This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 644869-DICE info:eu-repo/grantAgreement/EC/H2020/644869/EU/Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements/DICE info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 1.806 2017 COMPUTER SCIENCE, SOFTWARE ENGINEERING 32 / 104 = 0.308 2017 Q2 T1 0.317 2017 Software 2017 Q3 info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 24 (2017), 73-99 Automated Software Engineering Automated Software Engineering 0928-8910 2318332 http://zaguan.unizar.es/record/57744/files/texto_completo.pdf Preprint 6567 http://zaguan.unizar.es/record/57744/files/texto_completo.jpg?subformat=icon icon Preprint oai:zaguan.unizar.es:57744 articulos driver 2019-07-09-11:25:03 ARTICLE