expert-guided automatic diagnosis of performance problems in enterprise applications

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Authors and Contributors (sorted by last name)

Tobias Angerstein (tangerstein), Jakob Benz (@jakobbenz), Alexander Bran (@branalex), Thomas Düllman (@duelle), Christoph Heger (@hegerchr), Alper Hidiroglu (@alperhi), André van Hoorn (@avanhoorn), Jonas Kunz (@jonas163), Dušan Okanović (@okism), Marius Oehler (@mariusoe), Manuel Palenga (@manuelpalenga), Henning Schulz (@henning-schulz), Ivan Senic (@ivansenic), Stefan Siegl (@stefansiegl), Teerat Pitakrat (@teeratpitakrat), Claudio Waldvogel (@ClaudioWaldvogel), Alexander Wert (@alexanderwert)

How to become a contributor

You can contribute to the diagnoseIT project by forking our repository on GitHub, signing the contributor agreement and creating a merge request to merge your contribution into the main repository.

For students, we offer the opportunity to contribute in the form of doing a bachelor or master thesis in the context of the diagnoseIT project. Have a look at the list of running, completed, and open theses on the publications page.

International Collaboration on Deteting Antipatterns from Profiler Data

Since 2016, we are involved in an international collaboration on exploiting load testing and profiling for performance antipattern detection. The collaboration resulted from a breakout group at the GI-Dagstuhl Seminar 16394 (Software Performance Engineering in the DevOps World). Members of the collaboration are Catia Trubiani (GSSI, Italy; head), Alberto Avritzer (USA), Alexander Bran (University of Stuttgart, Germany), Andre van Hoorn (University of Stuttgart, Germany), and Holger Knoche (Kiel University, Germany). A first output of the collaboration is the journal publication