164 citations · 250 across the 9 of their papers we have counts for
9 papers
A/B Testing: A Systematic Literature Review
Federico Quin, Danny Weyns, Matthias Galster +1
In A/B testing two variants of a piece of software are compared in the field from an end user's point of view, enabling data-driven decision making. While widely used in practice,…
Reducing Large Adaptation Spaces in Self-Adaptive Systems Using Machine Learning
Federico Quin, Danny Weyns, Omid Gheibi
Modern software systems often have to cope with uncertain operation conditions, such as changing workloads or fluctuating interference in a wireless network. To ensure that these s…
Automating Pipelines of A/B Tests with Population Split Using Self-Adaptation and Machine Learning
Federico Quin, Danny Weyns
A/B testing is a common approach used in industry to facilitate innovation through the introduction of new features or the modification of existing software. Traditionally, A/B tes…
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…
Deep Learning for Effective and Efficient Reduction of Large Adaptation Spaces in Self-Adaptive Systems
Danny Weyns, Omid Gheibi, Federico Quin +1
Many software systems today face uncertain operating conditions, such as sudden changes in the availability of resources or unexpected user behavior. Without proper mitigation thes…
SEAByTE: A Self-adaptive Micro-service System Artifact for Automating A/B Testing
Federico Quin, Danny Weyns
Micro-services are a common architectural approach to software development today. An indispensable tool for evolving micro-service systems is A/B testing. In A/B testing, two varia…
On the Impact of Applying Machine Learning in the Decision-Making of Self-Adaptive Systems
Omid Gheibi, Danny Weyns, Federico Quin
Recently, we have been witnessing an increasing use of machine learning methods in self-adaptive systems. Machine learning methods offer a variety of use cases for supporting self-…
Decentralized Self-Adaptive Systems: A Mapping Study
Federico Quin, Danny Weyns, Omid Gheibi
With the increasing ubiquity and scale of self-adaptive systems, there is a growing need to decentralize the functionality that realizes self-adaptation. Our focus is on architectu…
Applying Machine Learning in Self-Adaptive Systems: A Systematic Literature Review
Omid Gheibi, Danny Weyns, Federico Quin
Recently, we witness a rapid increase in the use of machine learning in self-adaptive systems. Machine learning has been used for a variety of reasons, ranging from learning a mode…