Going Online: Reflections on Testing Machine Learning Based Systems
Modern smart software-intensive systems in domains like manufacturing, health, or automotive, are data-intensive, autonomous, critical, and enabled by machine-learning-based AI, which poses new quality and trustworthiness challenges. Therefore, new so called online testing approaches are needed, where machine learning components are embedded into a specific application environment and tested in a closed-loop mode in interaction with the application environment. In this talk, we provide an overview of current results and highlight research challenges in this field
Slides (Felderer_TestAutomationAI.pdf) | 3.19MiB |
Michael Felderer is a professor at the Department of Computer Science at the University of Innsbruck, Austria and a senior researcher at the Department of Software Engineering at the Blekinge Institute of Technology, Sweden. In 2014 he was a guest researcher at Lund University, Sweden and in 2015 a guest lecturer at the University of Stuttgart, Germany. His fields of expertise and interest include software quality, testing, software and security processes, risk management, software analytics and measurement, requirements engineering, model-based software engineering and empirical research methodology in software and security engineering. Michael Felderer holds a habilitation degree from the University of Innsbruck, co-authored more than 130 publications and received 9 best paper awards. His research has a strong empirical focus also using methods of data science and is directed towards development and evaluation of efficient and effective methods to improve quality and value of industrial software systems and processes in close collaboration with companies. Michael Felderer himself has more than 10 years of industrial experience as a senior executive consultant, project manager and software engineer. He is an internationally recognized member of the software engineering research community and supports it as an editorial board member, organizer of conferences (e.g. General Chair of PROFES 2017) and regular PC member of premier conferences. For more information visit his website at mfelderer.at.
Tue 17 MayDisplayed time zone: Eastern Time (US & Canada) change
10:50 - 11:50 | |||
10:50 60mKeynote | Going Online: Reflections on Testing Machine Learning Based Systems AST 2022 Michael Felderer University of Innsbruck File Attached |