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Journal ArticleSimona Bernardi, Juan L. Domínguez, Abel Gómez, Christophe Joubert, José Merseguer, Diego Perez-Palacin, José I. Requeno, Alberto Romeu
In: Empirical Software Engineering, vol. 23, no. 6, pp. 3394–3441, 2018, ISSN: 1573-7616.
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.
ConferenceAbel Gómez, José Merseguer
Actas de las XXI Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2016), SISTEDES, Salamanca, Spain, 2016.
Tags: Computer Aided Design (CASE), Data-Intensive Applications (DIA), DICE, Model-Driven Engineering (MDE), Modeling and Analysis of Real Time and Embedded systems (MARTE), Petri net (PN), Simulation, UML Profiles, Unified Modeling Language (UML)| | |
Las aplicaciones intensivas en datos (AID) que usan tecnologías de Big Data se están convirtiendo en una parte importante del mercado de desarrollo de software. Sin embargo, las técnicas --y su automatización-- para el asesoramiento de la calidad para este tipo de aplicaciones es claramente insuficiente. El proyecto DICE H2020 tiene como objetivo definir metodologías y crear herramientas para desarrollar y monitorizar AID mediante técnicas de ingeniería dirigida por modelos. En este artículo presentamos un componente clave del proyecto DICE: su herramienta de simulación. Esta herramienta es capaz de evaluar el rendimiento de AID simulando su comportamiento mediante modelos de redes de Petri. Como complemento, existe a disposición un vídeo mostrando la herramienta en http://tiny.cc/z1qzay.
ConferenceAbel Gómez, José Merseguer, Elisabetta Di Nitto, Damian A. Tamburri
Proceedings of the 2nd International Workshop on Quality-Aware DevOps, co-located with ACM SIGSOFT International Symposium on Software Testing and Analysis 2016 (ISSTA'16), QUDOS 2016 ACM, New York, NY, USA, 2016, ISBN: 978-1-4503-4411-1, (Saarbrücken, Germany).
Tags: Computer Aided Design (CASE), Data-Intensive Applications (DIA), DICE, Model-Driven Engineering (MDE), Modeling and Analysis of Real Time and Embedded systems (MARTE), UML Profiles, Unified Modeling Language (UML)| | |
Data intensive applications that leverage Big Data technologies are rapidly gaining market trend. However, their design and quality assurance are far from satisfying software engineers needs. In fact, a CapGemini research shows that only 13% of organizations have achieved full-scale production for their Big Data implementations. We aim at addressing an early design and a quality evaluation of data intensive applications,being our goal to help software engineers on assessing quality metrics, such as the response time of theapplication. We address this goal by means of a quality analysis tool-chain.At the core of the tool, we are developing a Profile that converts the Unified Modeling Language into a domain specific modeling language for quality evaluation of data intensive applications.
ConferenceAbel Gómez, Christophe Joubert, José Merseguer
Actas de las XXIV Jornadas de Concurrencia y Sistemas Distribuidos (JCSD 2016), Godel S. L., Granada, Spain, 2016, ISBN: 978-84-16478-90-3.
Tags: Computer Aided Design (CASE), Data-Intensive Applications (DIA), DICE, Modeling and Analysis of Real Time and Embedded systems (MARTE), Petri net (PN), Posidonia Operations, UML Profiles, Unified Modeling Language (UML)| | |
Big Data is becoming a core asset for present economy and businesses, and as such, Data-Intensive Applications (DIA) that use Big Data technologies are becoming crucial products in the software development market. However, quality assurance of such applications is still an open issue. The H2020 DICE project aims to define a quality-driven framework for developing DIA based on model-driven engineering (MDE) techniques. In this paper we present a key component of the DICE Framework, the DICE Simulation Tool. The tool is able to simulate the behavior of a DIA to assess its performance using a Petri net model. To showcase its capabilities we use the Posidonia Operations case study, a real-world scenario brought from one of our industrial partners. In addition to this paper, a video demonstrating the tool is available at http://tiny.cc/z1qzay.