| 1. |
- Bernardi, Simona, et al.
(författare)
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A systematic approach for performance assessment using process mining : An industrial experience report
- 2018
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Ingår i: Empirical Software Engineering. - : Springer. - 1382-3256 .- 1573-7616. ; 23:6, s. 3394-3441
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
- Bernardi, Simona, et al.
(författare)
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DICE simulation : a tool for software performance assessment at the design stage
- 2022
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Ingår i: Automated Software Engineering. - : Springer. - 0928-8910 .- 1573-7535. ; 29
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, we have seen many performance fiascos in the deployment of new systems, such as the US health insurance web. This paper describes the functionality and architecture, as well as success stories, of a tool that helps address these types of issues. The tool allows assessing software designs regarding quality, in particular performance and reliability. Starting from a UML design with quality annotations, the tool applies model-transformation techniques to yield analyzable models. Such models are then leveraged by the tool to compute quality metrics. Finally, quality results, over the design, are presented to the engineer, in terms of the problem domain. Hence, the tool is an asset for the software engineer to evaluate system quality through software designs. While leveraging the Eclipse platform, the tool uses UML and the MARTE, DAM and DICE profiles for the system design and the quality modeling.
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| 3. |
- Perez-Palacin, Diego, et al.
(författare)
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A UML Profile for the Design, Quality Assessment and Deployment of Data-intensive Applications
- 2019
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Ingår i: Software and Systems Modeling. - : Springer. - 1619-1366 .- 1619-1374. ; 18:6, s. 3577-3614
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Tidskriftsartikel (refereegranskat)abstract
- Big Data or Data-Intensive applications (DIAs) seek to mine, manipulate, extract or otherwise exploit the potential intelligence hidden behind Big Data. However, several practitioner surveys remark that DIAs potential is still untapped because of very difficult and costly design, quality assessment and continuous refinement. To address the above shortcoming, we propose the use of a UML domain-specific modeling language or profile specifically tailored to support the design, assessment and continuous deployment of DIAs. This article illustrates our DIA-specific profile and outlines its usage in the context of DIA performance engineering and deployment. For DIA performance engineering, we rely on the Apache Hadoop technology, while for DIA deployment, we leverage the TOSCA language. We conclude that the proposed profile offers a powerful language for data-intensive software and systems modeling, quality evaluation and automated deployment of DIAs on private or public clouds.
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| 4. |
- Requeno, José I., et al.
(författare)
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Quantitative Analysis of Apache Storm Applications : The NewsAsset Case Study
- 2019
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Ingår i: Information Systems Frontiers. - Berlin/Heidelberg : Springer. - 1387-3326 .- 1572-9419. ; 21:1, s. 67-85
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Tidskriftsartikel (refereegranskat)abstract
- The development of Information Systems today faces the era of Big Data. Large volumes of information need to be processed in real-time, for example, for Facebook or Twitter analysis. This paper addresses the redesign of NewsAsset, a commercial product that helps journalists by providing services, which analyzes millions of media items from the social network in real-time. Technologies like Apache Storm can help enormously in this context. We have quantitatively analyzed the new design of NewsAsset to assess whether the introduction of Apache Storm can meet the demanding performance requirements of this media product. Our assessment approach, guided by the Unified Modeling Language (UML), takes advantage, for performance analysis, of the software designs already used for development. In addition, we converted UML into a domain-specific modeling language (DSML) for Apache Storm, thus creating a profile for Storm. Later, we transformed said DSML into an appropriate language for performance evaluation, specifically, stochastic Petri nets. The assessment ended with a successful software design that certainly met the scalability requirements of NewsAsset.
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