Browsing by Author "Weilinger, Matthias"

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Open Access
Design and implementation of a service recommendation system for Clams
(2021) Weilinger, Matthias
Cloud computing has been on the rise for years and will not stop following this trend in the future. Developers must have an environment where they can design cloud applications and receive feedback on the Quality of Service their design provides. This thesis aims to provide a framework that calculates the availability of a software design based on a given reliability model. First, this work describes the essential principles needed to understand the model and the calculations. This includes scenarios, Message Sequence Charts, and Labelled Transition Systems. Then it describes the implementation of a scenario-based reliability model in detail. Additionally, I propose an algorithm that maximizes the availability value by recommending suitable services based on the availability model. The performance and precision of the implementation are then evaluated. We will see that the precision is accurate, and the number and density of transactions between cloud services influence the runtime the most. Finally, I summarize the found results and look at the future developments of the topic.
Open Access
Implementing variational quantum algorithms as compositions of reusable microservice-based plugins
(2023) Weilinger, Matthias
With its transformative processing capabilities, Quantum computing has ushered in a new computational era, presenting unparalleled opportunities and intricate challenges. One potential beneficiary of this quantum revolution is the Digital Humanities. With quantum computing, the field has the potential to enhance its quantitative analysis dramatically. QHAna, the Quantum Humanities Analysis tool explicitly designed for Quantum Digital Humanities, emerges as a pivotal system. This thesis focuses on enhancing QHAna by integrating variational algorithms and paving the way for Variational Quantum Algorithms in a modular manner. The objective is to encapsulate components of variational algorithms as distinct, interchangeable plugins, ensuring adaptability and enabling end users to adapt the algorithms. Addressing challenges like robust plugin communication and intuitive user experience, the research delves into this modular framework's design, implementation, and evaluation. Beyond the immediate application to Variational Quantum Algorithms, the insights and methodologies derived here lay the foundational groundwork for future modular system designs in the quantum computing domain.