ConferenceSimona Bernardi, Juan L. Domínguez, Abel Gómez, Christophe Joubert, José Merseguer, Diego Perez-Palacin, José I. Requeno, Alberto Romeu A Systematic Approach for Performance Assessment Using Process Mining: An Industrial Experience Report (Abstract) Actas de las XXIV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2019), Cáceres, septiembre de 2019., Sistedes Sistedes, 2019. Abstract | Links | BibTeX | Tags: Complex Event Processing (CEP), Petri net (PN), Process Mining, Software Perfomance, Unified Modeling Language (UML) @conference{Bernardi:JISBD:2019,
title = {A Systematic Approach for Performance Assessment Using Process Mining: An Industrial Experience Report (Abstract)},
author = {Simona Bernardi and Juan L. Dom\'{i}nguez and Abel G\'{o}mez and Christophe Joubert and Jos\'{e} Merseguer and Diego Perez-Palacin and Jos\'{e} I. Requeno and Alberto Romeu},
editor = {Jennifer P\'{e}rez },
url = {http://hdl.handle.net/11705/JISBD/2019/019},
year = {2019},
date = {2019-09-02},
booktitle = {Actas de las XXIV Jornadas de Ingenier\'{i}a del Software y Bases de Datos (JISBD 2019), C\'{a}ceres, septiembre de 2019.},
publisher = {Sistedes},
organization = {Sistedes},
abstract = {Software 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.},
keywords = {Complex Event Processing (CEP), Petri net (PN), Process Mining, Software Perfomance, Unified Modeling Language (UML)},
pubstate = {published},
tppubtype = {conference}
}
Software 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. AbstractOpen Access |
Journal ArticleSimona Bernardi, Juan L. Domínguez, Abel Gómez, Christophe Joubert, José Merseguer, Diego Perez-Palacin, José I. Requeno, Alberto Romeu A systematic approach for performance assessment using process mining: An industrial experience report In: Empirical Software Engineering, vol. 23, no. 6, pp. 3394–3441, 2018, ISSN: 1573-7616. Abstract | Links | BibTeX | Tags: DICE, Experience Report, Modeling and Analysis of Real Time and Embedded systems (MARTE), Petri net (PN), Process Mining, Simulation, Software Perfomance, Unified Modeling Language (UML) @article{Bernardi:EmSE:2018,
title = {A systematic approach for performance assessment using process mining: An industrial experience report},
author = {Simona Bernardi and Juan L. Dom\'{i}nguez and Abel G\'{o}mez and Christophe Joubert and Jos\'{e} Merseguer and Diego Perez-Palacin and Jos\'{e} I. Requeno and Alberto Romeu},
url = {http://rdcu.be/Jz3J},
doi = {10.1007/s10664-018-9606-9},
issn = {1573-7616},
year = {2018},
date = {2018-03-21},
journal = {Empirical Software Engineering},
volume = {23},
number = {6},
pages = {3394--3441},
abstract = {Software 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.},
keywords = {DICE, Experience Report, Modeling and Analysis of Real Time and Embedded systems (MARTE), Petri net (PN), Process Mining, Simulation, Software Perfomance, Unified Modeling Language (UML)},
pubstate = {published},
tppubtype = {article}
}
Software 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. |