000069759 001__ 69759
000069759 005__ 20200513005820.0
000069759 0247_ $$2doi$$a10.1007/s10664-018-9606-9
000069759 0248_ $$2sideral$$a105273
000069759 037__ $$aART-2018-105273
000069759 041__ $$aeng
000069759 100__ $$0(orcid)0000-0002-2605-6243$$aBernardi, Simona$$uUniversidad de Zaragoza
000069759 245__ $$aA systematic approach for performance assessment using process mining. An industrial experience report
000069759 260__ $$c2018
000069759 5060_ $$aAccess copy available to the general public$$fUnrestricted
000069759 5203_ $$aSoftware performance engineering is a mature field that offers methods to assess system performance. Process mining is a promising research field applied to gain insight on system processes. The interplay of these two fields opens promising applications in the industry. In this work, we report our experience applying a methodology, based on process mining techniques, for the performance assessment of a commercial data-intensive software application. The methodology has successfully assessed the scalability of future versions of this system. Moreover, it has identified bottlenecks components and replication needs for fulfilling business rules. The system, an integrated port operations management system, has been developed by Prodevelop, a medium-sized software enterprise with high expertise in geospatial technologies. The performance assessment has been carried out by a team composed by practitioners and researchers. Finally, the paper offers a deep discussion on the lessons learned during the experience, that will be useful for practitioners to adopt the methodology and for researcher to find new routes.
000069759 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/TIN2014-58457-R$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 644869-DICE$$9info:eu-repo/grantAgreement/EC/H2020/644869/EU/Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements/DICE$$9info:eu-repo/grantAgreement/ES/DGA/T94
000069759 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000069759 590__ $$a4.457$$b2018
000069759 591__ $$aCOMPUTER SCIENCE, SOFTWARE ENGINEERING$$b8 / 107 = 0.075$$c2018$$dQ1$$eT1
000069759 592__ $$a0.62$$b2018
000069759 593__ $$aSoftware$$c2018$$dQ2
000069759 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000069759 700__ $$aDomínguez, J.
000069759 700__ $$aGómez, A.
000069759 700__ $$aJoubert, C.
000069759 700__ $$0(orcid)0000-0002-8917-6584$$aMerseguer, José$$uUniversidad de Zaragoza
000069759 700__ $$aPerez-Palacín, D.
000069759 700__ $$0(orcid)0000-0001-5111-8357$$aRequeno, J.$$uUniversidad de Zaragoza
000069759 700__ $$aRomeu, A.
000069759 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000069759 773__ $$g23 (2018), 3394 – 3441$$pEmpir. Softw. Eng.$$tEMPIRICAL SOFTWARE ENGINEERING$$x1382-3256
000069759 8564_ $$s1865606$$uhttps://zaguan.unizar.es/record/69759/files/texto_completo.pdf$$yPreprint
000069759 8564_ $$s57310$$uhttps://zaguan.unizar.es/record/69759/files/texto_completo.jpg?subformat=icon$$xicon$$yPreprint
000069759 909CO $$ooai:zaguan.unizar.es:69759$$particulos$$pdriver
000069759 951__ $$a2020-05-13-00:49:08
000069759 980__ $$aARTICLE