%0 Conference Paper %1 GoBrKo2013-ControllingPCM %A Gorsler, Fabian %A Brosig, Fabian %A Kounev, Samuel %B Proceedings of the Symposium on Software Performance: Joint Kieker/Palladio Days (KPDAYS 2013) %C Aachen, Germany %D 2013 %E Becker, Steffen %E Hasselbring, Wilhelm %E van Hoorn, André %E Reussner, Ralf %I CEUR-WS.org %K Analytical_and_simulation-based_analysis Application_quality_of_service_management DQL Formal_architecture_modeling Optimization Performance Prediction Resource_management Simulation Tool descartes t_workshop myown %N 1083 %P 109--118 %T Controlling the Palladio Bench using the Descartes Query Language %U http://ceur-ws.org/Vol-1083/ %X The Palladio Bench is a tool to model, simulate and analyze Palladio Component Model (PCM) instances. However, for the Palladio Bench, no single interface to automate experiments or Application Programming Interface (API) to trigger the simulation of PCM instances and to extract performance prediction results is available. The Descartes Query Language (DQL) is a novel approach of a declarative query language to integrate different performance modeling and prediction techniques behind a unifying interface. Users benefit from the abstraction of specific tools to prepare and trigger performance predictions, less effort to obtain performance metrics of interest, and means to automate performance predictions. In this paper, we describe the realization of a DQL Connector for PCM and demonstrate the applicability of our approach in a case study.

@inproceedings{GoBrKo2013-ControllingPCM, abstract = {The Palladio Bench is a tool to model, simulate and analyze Palladio Component Model (PCM) instances. However, for the Palladio Bench, no single interface to automate experiments or Application Programming Interface (API) to trigger the simulation of PCM instances and to extract performance prediction results is available. The Descartes Query Language (DQL) is a novel approach of a declarative query language to integrate different performance modeling and prediction techniques behind a unifying interface. Users benefit from the abstraction of specific tools to prepare and trigger performance predictions, less effort to obtain performance metrics of interest, and means to automate performance predictions. In this paper, we describe the realization of a DQL Connector for PCM and demonstrate the applicability of our approach in a case study.}, added-at = {2020-04-05T23:09:36.000+0200}, address = {Aachen, Germany}, author = {Gorsler, Fabian and Brosig, Fabian and Kounev, Samuel}, biburl = {https://www.bibsonomy.org/bibtex/2070b699841a9caa32e23460c5fc82d41/samuel.kounev}, booktitle = {Proceedings of the Symposium on Software Performance: Joint Kieker/Palladio Days (KPDAYS 2013)}, editor = {Becker, Steffen and Hasselbring, Wilhelm and van Hoorn, Andr{\'e} and Reussner, Ralf}, interhash = {34bce48ba5a444eb670a77c6298d6edc}, intrahash = {070b699841a9caa32e23460c5fc82d41}, keywords = {Analytical_and_simulation-based_analysis Application_quality_of_service_management DQL Formal_architecture_modeling Optimization Performance Prediction Resource_management Simulation Tool descartes t_workshop myown}, month = {November}, number = 1083, pages = {109--118}, publisher = {CEUR-WS.org}, timestamp = {2020-10-21T04:00:44.000+0200}, title = {Controlling the Palladio Bench using the Descartes Query Language}, url = {http://ceur-ws.org/Vol-1083/}, year = 2013 }