Providing Model-Extraction-as-a-Service for Architectural Performance Models
Autor(en):
Zusammenfassung
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 significant 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.
- Vollständige Referenz
- BibTeX
Walter, J., Eismann, S., Reed, N. & Kounev, Sa.,
(2017).
Providing Model-Extraction-as-a-Service for Architectural Performance Models.
Softwaretechnik-Trends Band 37, Heft 3.
Bonn:
Geselllschaft für Informatik e.V..
(S. 8-10).
@inproceedings{mci/Walter2017,
author = {Walter, Jürgen AND Eismann, Simon AND Reed, Nikolai AND Kounev,Samuel},
title = {Providing Model-Extraction-as-a-Service for Architectural Performance Models},
booktitle = {Softwaretechnik-Trends Band 37, Heft 3},
year = {2017},
editor = {} ,
pages = { 8-10 },
publisher = {Geselllschaft für Informatik e.V.},
address = {Bonn}
}
author = {Walter, Jürgen AND Eismann, Simon AND Reed, Nikolai AND Kounev,Samuel},
title = {Providing Model-Extraction-as-a-Service for Architectural Performance Models},
booktitle = {Softwaretechnik-Trends Band 37, Heft 3},
year = {2017},
editor = {} ,
pages = { 8-10 },
publisher = {Geselllschaft für Informatik e.V.},
address = {Bonn}
}
| Dateien | Groesse | Format | Anzeige | |
|---|---|---|---|---|
| 02_Providing_Model-Extraction-as-a-Service_for_Architectural_Performance_Models.pdf | 270.2Kb | Öffnen |
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Mehr Information
ISSN: 0720-8928
Datum: 2017
Sprache:
(en)
(en)
Typ: Journal Articles

