In this paper, we extend our ensemble-based component model DEECo with the capability
to use machine-learning and optimization heuristics in establishing and reconfiguration of …

Simulation is a powerful process for perfectly planning and dimensioning web systems.
However, a successful analysis using a simulation model usually requires variable load …

This paper features an approach that combines machine-learning abstractions with a
component model. We target modern self-optimizing systems and therefore integrate the …

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing
dependability based on architectural models of software-intensive systems early in …

Abstract Machine learning (ML) has shown its potential in extending the ability of self-
adaptive systems to deal with unknowns. To date, there have been several approaches to …

Serverless computing has gained popularity in recent years, and it is being used in an
increasing number of use cases. It is still limited by some of its challenges, such as high …

System performance is getting attention by industry as it affects user experience, and much
research focused on performance evaluation approaches. Profiling is the most …

Serverless computing is an emerging cloud computing paradigm that offers a highlevel
application programming model with utilization-based billing. It enables the deployment of …

Machine learning (ML) has shown its potential in extending the ability of self-adaptive
systems to deal with unknowns. To date, there have been several approaches to applying …

Software systems execute tasks that depend on different types of resources. However, the
variability of resources may interfere with the ability of software systems to execute important …