In this study, we evaluate predictive modelling techniques within project management, employing diverse architectures such as the LSTM, CNN, CNN-LSTM, GRU, MLP, and RNN models. The primary focus is on assessing the precision and consistency of predictions for crucial project parameters, including completion time, required personnel, and estimated costs. Our analysis utilises a comprehensive dataset that encapsulates the complexities inherent in real-world projects, providing a robust basis for evaluating model performance. The findings, presented through detailed tables and comparative charts, underscore the collective success of the models. The LSTM model stands out for its exceptional performance in consistently predicting completion time, personnel requirements, and estimated costs. Quantitative evaluation metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE), corroborate the efficacy of the models. This study offers insights into the success observed, reflecting the potential for further refinement and continuous exploration to enhance the accuracy of predictive models in the ever-evolving landscape of project management.

This paper deals with graph theory application in large-scale geographical data searching and visualization. We present a comparison of two path-finding algorithms of graph theory, i.e. blind-search and A* algorithm, that results into the selection of the second one for implementation within a geographical information system. The main goal is to process the terrain map representation in the form of a graph during route-searching between start and target positions, and during the visualization and animation of the results of this search. We show the implementation results on random city map and on real three-dimensional model of our university campus. Finally, we discuss further directions of current work.

3D model creation and visualization is often used in digital preservation of looks and structure of historical buildings. Virtual reality (VR) technologies facilitate this 3D model creation and visualization. 3D scanner can be used for acceleration of the data collection and model creation. 3D displays can be used to improve visual perception and 3D printing can be used for physical model creation. In this paper is presented the way for preservation of historical buildings using virtual reality technologies. Example of preservation procedure, which consists from 3D scanning, 3D model creation, optimization and visualization, is shown on the historical building of The State Theatre of Košice.

Software quality assurance is very important in each software project. As part of this quality assurance, testing is applied and testware are used. Current trends in software development show that cloud architectures are becoming preferred over classical software architectures. To follow this trend, we propose an architectural prototype of a testware as a service (TaaS). In current paper, we present the architectural blueprint of our TaaS and initial results of its implementation.

The widespread usage of mobile devices has made rapid progress recently in the society. The gradual development, modification and improvement of mobile applications is a rule. This contribution presents the application of refactoring and regression testing, which supports the software modification in a systematic and controlled manner. The database refactoring and regression testing is presented within the development of an experimental mobile Android-based application. Finally, the contribution evaluates the results of the experiments and verifies their correctness.