doc. Ing. Tomáš Vitvar, Ph.D.

System infrastructures including operating systems, networking, web servers, load balancers, application servers, etc. produce massive amounts of operations data during systems runtime. Operations data science aims to improve various machine learning methods to help understand patterns, correlations or similarities from the past systems’ behavior in order to improve operations practice, for example, systems maintenance, changes in systems design or root cause analysis of incidents. This includes predicting systems behaviors when unplanned or unexpected events occur such as connectivity lost, failures of servers or spikes in systems workloads. This research will improve supervised and unsupervised learning methods tailored for problems from operational data analytics and cover a wide spectrum of underlying machine learning tasks including classification, clustering or regression.

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Jaroslav Kuchař, Ph.D.

Department of Software Engineering

This bachelor thesis analyzes an air-to-water heat pump system assisted by a solar panel, focusing on its operation, utilization, and necessary performance metrics. The thesis provides an overview of a specific system, analyzing trends in energy consumption and efficiency and identifying reasons for lower efficiency in the summer season. Additionally, the impact of various factors on the system's efficiency and electricity consumption is assessed, with temperature having the greatest influence on efficiency and compressor speed having the most significant impact on energy consumption. Afterwards, the most influential factors were used for predictions. The investment in a heat pump is advantageous compared to alternative investment options, particularly with the grant obtained, and can be comparable to investing in stocks in some cases.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Karel Klouda, Ph.D.

Department of Applied Mathematics

This thesis investigates patterns in user interfaces, also known as dark patterns, that force users to do things or make decisions differently than they originally intended. This thesis focuses on the detection of dark patterns used by webshops on the Czech Internet and the detection is done on a large scale. This thesis builds on research already conducted at Princeton University that investigated dark patterns on English webshops. Several tools were created to retrieve a significant number of webshops. Also the tools from the conducted research were modified to be applied to the Czech language. These tools were used to obtain multiple datasets mapping webshops on the Czech Internet and the dark patterns used on them. It was found that dark patterns are widely used on Czech webshops.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Zdeněk Rybola, Ph.D.

Department of Software Engineering

This thesis is focused on the integration of reservation systems for sport facilities. The work starts with a survey and analysis of the existing reservation systems for sport facilities. Next there is an analysis of integration of reservation systems for hotels. Afterthat I proposed functional requirements, data model, system architecture and interfaces for integration. The next sections describe the system implementation and system testing.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Milan Dojčinovski, Ph.D.

Department of Software Engineering

The goal of this thesis is to build a web application that would represent a complete solution to the process of creating, taking and evaluating exams. Apart from providing an overview of the implementation, the text tries to describe in detail the decisions that were made while developing the application and to introduce to the reader the many ideas these decisions were based on.

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Zdeněk Troníček, Ph.D.

Department of Software Engineering

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Zdeněk Troníček, Ph.D.

Department of Software Engineering

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Milan Dojčinovski, Ph.D.

Department of Software Engineering

Video learning material indexes are rare and could lead to a better studying experience for students. This thesis aims to implement a web service for video lecture indexing with the help of supplementary materials as user input with focus on FIT CTU courses. The result is a deployed web service capable of video lecture indexing with satisfactory accuracy on the testing dataset, providing API, UI and core module with algorithm as a Python package.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Jaroslav Kuchař, Ph.D.

Department of Software Engineering

Currently, information systems from the infrastructural point of view containing operating systems, web servers, application servers, load balancers, network communication elements produce a huge amount of operations data and write it to logs. Analysis of such logs can help to understand the current state of the system -- for instance, to determine the places, when errors occur. Such a knowledge helps to improve the performance of the system, make it more stable and accessible. Human is not able to read, analyze and process such a number of messages in a reasonable time, so it makes sense to perform a cluster analysis on server log files. Several groups (clusters) of similar log messages will be generated after clustering. This approach allows to significantly reduce the dimension of original log data, and allows to analyze not individual log entries, but groups, which simplifies searching and elimination of problems that have arisen during the server runtime. This thesis proposes software for server log clustering based on natural language processing and machine-generated text processing techniques and machine learning algorithms, followed by the analysis of clustered log data.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Jiří Mlejnek

Department of Software Engineering

Microservices architecture have become a ubiquitous standard in the software industry, where they are often used as a one-size-fits-all solution, disregarding their drawbacks. This thesis aims to analyse the design approaches of monolithic, microservices and modern modular architecture and compare them, while emphasising the frequently overlooked negative consequences of Microservices in favour of Modular Monolith architecture. The author discusses his experience working on microservices projects and the challenges they faced with the architecture in practice. A proof of concept application is developed for each type of architecture mentioned and thoroughly analysed for performance and latency. Finally, the thesis concludes by presenting a methodology for employing the Modular Monolith architecture approach in new projects and how the said architecture can evolve throughout the application lifecycle.

Thesis on DSpace

doc. Ing. Tomáš Vitvar, Ph.D.

Ing. Zdeněk Troníček, Ph.D.

Department of Software Engineering