%0 Conference Paper %1 WaEiReKo2017-SPP-MEaaS %A Walter, Jürgen %A Eismann, Simon %A Reed, Nikolai %A Kounev, Samuel %B Proceedings of the 2017 Symposium on Software Performance (SSP) %D 2017 %K t_workshop Performance Automated_model_learning DECLARE myown PMX Tool descartes DML %T Providing Model-Extraction-as-a-Service for Architectural Performance Models %X Architectural performance models can be leveraged to explore performance properties of software systems during design-time and run-time. We see a reluctance from industry to adopt model-based analysis approaches due to the required expertise and modeling effort. Building models from scratch in an editor does not scale for medium and large-scale systems in an industrial context. Existing open-source performance model extraction approaches imply signi cant initial efforts which might be challenging for layman users. To simplify usage, we provide the extraction of architectural performance models based on application monitoring traces as a web service. Model-Extraction-as-a-Service (MEaaS) solves the usability problem and lowers the initial effort of applying model-based analysis approaches.

@inproceedings{WaEiReKo2017-SPP-MEaaS, abstract = {Architectural performance models can be leveraged to explore performance properties of software systems during design-time and run-time. We see a reluctance from industry to adopt model-based analysis approaches due to the required expertise and modeling effort. Building models from scratch in an editor does not scale for medium and large-scale systems in an industrial context. Existing open-source performance model extraction approaches imply signi cant initial efforts which might be challenging for layman users. To simplify usage, we provide the extraction of architectural performance models based on application monitoring traces as a web service. Model-Extraction-as-a-Service (MEaaS) solves the usability problem and lowers the initial effort of applying model-based analysis approaches.}, added-at = {2020-04-05T23:12:16.000+0200}, author = {Walter, J{\"u}rgen and Eismann, Simon and Reed, Nikolai and Kounev, Samuel}, biburl = {https://www.bibsonomy.org/bibtex/2d16a0d53c2bfd95fdf0f1ab776e6d28c/samuel.kounev}, booktitle = {Proceedings of the 2017 Symposium on Software Performance (SSP)}, interhash = {27d7632708224f9b6c8d09fae9f3e2b3}, intrahash = {d16a0d53c2bfd95fdf0f1ab776e6d28c}, keywords = {t_workshop Performance Automated_model_learning DECLARE myown PMX Tool descartes DML}, month = {11}, timestamp = {2020-10-05T16:31:02.000+0200}, title = {{Providing Model-Extraction-as-a-Service for Architectural Performance Models}}, year = 2017 }