50 citations · 90 across the 10 of their papers we have counts for
13 papers
Towards Continuous Experiment-driven MLOps
Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos +5
Despite advancements in MLOps and AutoML, ML development still remains challenging for data scientists. First, there is poor support for and limited control over optimizing and evo…
SUAVE: An Exemplar for Self-Adaptive Underwater Vehicles
Gustavo Rezende Silva, Juliane Päßler, Jeroen Zwanepol +5
Once deployed in the real world, autonomous underwater vehicles (AUVs) are out of reach for human supervision yet need to take decisions to adapt to unstable and unpredictable envi…
Self-Adaptation in Industry: A Survey
Danny Weyns, Ilias Gerostathopoulos, Nadeem Abbas +13
Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the…
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation
Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova +16
Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introdu…
Preliminary Results of a Survey on the Use of Self-Adaptation in Industry
Danny Weyns, Ilias Gerostathopoulos, Nadeem Abbas +9
Self-adaptation equips a software system with a feedback loop that automates tasks that otherwise need to be performed by operators. Such feedback loops have found their way to a v…
Forming Ensembles at Runtime: A Machine Learning Approach
Tomáš Bureš, Ilias Gerostathopoulos, Petr Hnětynka +1
Smart system applications (SSAs) built on top of cyber-physical and socio-technical systems are increasingly composed of components that can work both autonomously and by cooperati…
How do we Evaluate Self-adaptive Software Systems?
Ilias Gerostathopoulos, Thomas Vogel, Danny Weyns +1
With the increase of research in self-adaptive systems, there is a need to better understand the way research contributions are evaluated. Such insights will support researchers to…
Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study
Justus Bogner, Roberto Verdecchia, Ilias Gerostathopoulos
Background: With the rising popularity of Artificial Intelligence (AI), there is a growing need to build large and complex AI-based systems in a cost-effective and manageable way.…
MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence
Vasileios Theodorou, Ilias Gerostathopoulos, Iyad Alshabani +2
Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspe…
Managing Latency in Edge-Cloud Environment
Lubomír Bulej, Tomáš Bureš, Adam Filandr +5
Modern Cyber-physical Systems (CPS) include applications like smart traffic, smart agriculture, smart power grid, etc. Commonly, these systems are distributed and composed of end-u…
Decentralized Optimization of Vehicle Route Planning -- A Cross-City Comparative Study
Brionna Davis, Grace Jennings, Taylor Pothast +3
New mobility concepts are at the forefront of research and innovation in smart cities. The introduction of connected and autonomous vehicles enables new possibilities in vehicle ro…
Engineering for a Science-Centric Experimentation Platform
Nikos Diamantopoulos, Jeffrey Wong, David Issa Mattos +4
Netflix is an internet entertainment service that routinely employs experimentation to guide strategy around product innovations. As Netflix grew, it had the opportunity to explore…
Planning as Optimization: Dynamically Discovering Optimal Configurations for Runtime Situations
Erik M. Fredericks, Ilias Gerostathopoulos, Christian Krupitzer +1
The large number of possible configurations of modern software-based systems, combined with the large number of possible environmental situations of such systems, prohibits enumera…