piwik-script

Intern
    Chair of Computer Science II - Software Engineering

    DQL

    Descartes Query Language

    Available approaches for performance prediction are usually based on their own modeling formalism and analysis tools. Users are forced to gain detailed knowledge about these approaches before predictions can be made. To lower these efforts, intermediate modeling approaches simplify the preparation and triggering of performance predictions. However, users still have to work with different tools suffering from integration, providing non-unified interfaces and the lack of interfaces to trigger performance predictions automatically.

    Our approach is to provide the Descartes Query Language capable of expressing queries for questions like “What is the response time of service X?”. Previous shortcomings are addressed by an interface to integrate different tools. The interface is accessible through a unified query language to trigger performance predictions. The design of the query language is based on a classification scheme with an implementation of an extensible architecture aiming to integrate a broad range of tools and third-party extensions. More information can be found on the following pages:

    If you have any questions, please contact Jürgen Walter.

     

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    Publications

    2018

    • Tools for Declarative Performance Engineering. J. Walter; S. Eismann; J. Grohmann; D. Okanovic; S. Kounev; in Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (2018). 53–56.
       

    2017

    • Automated and Adaptable Decision Support for Software Performance Engineering. J. Walter; A. van Hoorn; S. Kounev; in Proceedings of the 11th EAI International Conference on Performance Evaluation Methodologies and Tools (2017).
       
    • Mapping of Service Level Objectives to Performance Queries. J. Walter; D. Okanovic; S. Kounev; in Proceedings of the 2017 Workshop on Challenges in Performance Methods for Software Development (WOSP-C’17) co-located with 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017) (2017).
       
    • Model-Based Self-Aware Performance and Resource Management Using the Descartes Modeling Language. N. Huber; F. Brosig; S. Spinner; S. Kounev; M. Bähr; in IEEE Transactions on Software Engineering (TSE) (2017). 43(5) 432–452.
       

    2016

    • Extending the Descartes Query Language to Support Automated What-If Analysis. A. Knapp; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2016, August).
       
    • PAVO: A Framework for the Visualization of Performance Analyses Results. J. Walter; M. König; S. Eismann; S. Kounev; in Proceedings of the 2016 Symposium on Software Performance (SSP) (2016).
       
    • Kieker4DQL: Declarative Performance Measurement. M. Blohm; M. Pahlberg; S. Vogel; J. Walter; D. Okanovic; in Proceedings of the 2016 Symposium on Software Performance (SSP) (2016).
       
    • The Vision of Declarative Performance Engineering. J. Walter; A. van Hoorn; H. Koziolek; D. Okanovic; S. Kounev; in Proceedings of the 7th ACM/SPEC International Conference on Performance Engineering (ICPE 2016) (2016).
       
    • Automation and Simplification Through Declarative Performance Engineering. J. Walter; (2016, Juni).
       
    • Asking ``What?’’, Automating the ``How?’’: The Vision of Declarative Performance Engineering. J. Walter; A. van Hoorn; H. Koziolek; D. Okanovic; S. Kounev; in Proceedings of the 7th ACM/SPEC International Conference on Performance Engineering (ICPE 2016) (2016).
       

    2015

    • Declarative Automation Framework for QPME based on DQL. S. Eismann; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2015, März).
       

    2014

    • Performance Queries for Architecture-Level Performance Models. F. Gorsler; F. Brosig; S. Kounev; in Proceedings of the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014) (2014).
       

    2013

    • Online Performance Queries for Architecture-Level Performance Models. F. Gorsler; Thesis; Karlsruhe Institute of Technology (KIT); Am Fasanengarten 5, 76131 Karlsruhe, Germany. (2013, Juli).
       
    • Controlling the Palladio Bench using the Descartes Query Language. F. Gorsler; F. Brosig; S. Kounev; in Proceedings of the Symposium on Software Performance: Joint Kieker/Palladio Days (KPDAYS 2013), S. Becker, W. Hasselbring, A. van Hoorn, R. Reussner (Hrsg.) (2013). 109–118.