Volume 17 - 2025
Design and Implementation of a Static Analyzer for the Kotlin Programming Language
This paper presents the design and implementation of "Rough Analyzer," a static analysis tool for the Kotlin programming language. Modern software engineering requires writing scalable and maintainable code, and our tool assists in this by detecting code complexity, stylistic issues, and logical errors that the compiler often misses. The analyzer that we propose leverages abstract syntax tree traversal to identify issues such as high cyclomatic complexity, long functions, and magic numbers. The architecture is designed to be modular and easily extensible, allowing teams to add custom rules. We demonstrate the tool’s effectiveness on a real-world Kotlin project, showcasing its potential to improve code quality and reduce technical debt.
Example of a Hardware Challenge for an Ethical Hacking Competition
For the national ethical hacking competition, a hardware challenge was developed—a device based on the ESP32‑S3 microcontroller with intentionally introduced security vulnerabilities that participants must exploit across four tasks. The vulnerabilities on this device simulate issues commonly found in IoT and related devices: unprotected ports, firmware extraction and reverse engineering, insecure storage of cryptographic secrets, weak passwords, and insecure over‑the‑air updates.
Developing Infrastructure for Learning DevOps Development Principles
The adoption of DevOps development principles in software engineering education requires practical access to modern infrastructure, continuous integration and delivery systems, and monitoring platforms. This paper presents the design and implementation of a private cloud infrastructure developed at the School of Computer Science, University Union, Belgrade, Serbia to support learning of DevOps methodologies using open-source technologies.
The solution combines Kubernetes as the core orchestration platform with Kubermatic and KubeVirt platforms for cluster and virtualization management, enabling scalable, automated provisioning of environments for students and teaching staff. The implemented architecture provides real-world experience with infrastructure management, resource allocation, and deployment automation under limited academic resources.
The paper analyzes system performance, reliability, and maintenance aspects, highlights observed challenges such as virtualization overhead and cluster initialization latency and discusses alternative approaches using virtual Kubernetes clusters for further optimization and resource efficiency.
Examples of Scenarios for the Application of Explainable Artificial Intelligence in the Domain of Information Systems
In an era of increasingly intensive implementation of large language models within information systems, the issue of explainable artificial intelligence (XAI) has become crucial for maintaining trust, transparency, and ethical accountability. This paper examines methodological approaches to XAI in the context of both traditional AI and LLM-based models, focusing on their applicability, limitations, and role in meeting regulatory and ethical requirements. Through theoretical analysis, comparative evaluation of post-hoc and intrinsic methods, and practical insights involving models such as DistilBERT and GPT-5, the study illustrates how various XAI techniques can contribute to a deeper understanding of the behavior of complex AI systems. Particular emphasis is placed on five scenario-based examples of the development and testing of solutions in concrete organizational contexts. The application of XAI in information systems is further analyzed through the lens of credibility, stability, and usefulness criteria for explanations, as well as the challenges of integrating explainability into business information systems. The paper also addresses relevant regulatory frameworks and ethical implications that drive the advancement of XAI within the domain of information systems.
Analysis of Mobile Cloud Computing
Mobile Cloud Computing (MCC) is an emerging paradigm that integrates the advantages of mobile computing and cloud technologies to overcome the limitations of mobile devices such as limited processing power, storage, and battery life. This paper provides a comprehensive analysis of MCC, exploring its architecture, core technologies, benefits, and challenges. A particular focus is placed on the layered structure of MCC systems, including the mobile client, network, cloud infrastructure, and service management layers. The role of virtualization, mobile agents, and containerization in improving performance and reducing latency is also discussed.
The study compares three leading MCC platforms: Google Firebase, AWS Amplify, and Microsoft Azure Mobile Apps - highlighting their key functionalities, integration processes, and cost structures. A practical case study demonstrates the development of a prototype mobile application that scans cosmetic product barcodes and classifies ingredients based on their health safety, leveraging Firebase Cloud Functions and Firestore.
The findings indicate that MCC plays a vital role in the digital transformation of modern society, enabling scalable, accessible, and efficient mobile services. Nevertheless, ongoing advancements in security, legal frameworks, and collaborative efforts are essential for its sustainable and responsible deployment.
Development and Implementation of a Web Application for Buying and Selling Collectible Models
The aim of this work is to create a functional web application for buying and selling collectible models, taking into account the shortcomings of existing solutions, with the purpose of improving user experience and efficiency compared to the current market, as well as to present in detail the process of development and implementation of the proposed solution. The current market situation has been analyzed, highlighting the need for the development of such an application. Particular focus is placed on the application’s functionality and the way it is implemented. In addition, the application architecture, design decisions made during development, and a detailed overview of the technologies used are presented. The description also covers how the various functionalities were tested to ensure correctness and reliability. The result of this work is a detailed overview of the development and implementation of the application, along with an assessment of the achieved results, highlighting possibilities for further development and improvement of the solution. The developed application integrates all stages of the trading process into a single solution tailored to the specific niche of collectible models and represents an original contribution in this field, providing users with a practical, reliable, and efficient tool for trading.
Cloud Communication Software Architecture for Educational Institutions
This paper presents the design and implementation of a cloud-based communication software architecture, tailored for educational institutions. The system, RafBook-Backend, provides a unified platform for messaging, voice communication, user administration, and media sharing. Implemented in Java 17 using the Spring Boot framework, the solution integrates real-time communication technologies such as WebSocket, Firebase Cloud Messaging, and WebRTC for peer-to-peer audio channels. Data persistence is ensured with PostgreSQL, while Redis supports caching for performance optimization. The application is containerized with Docker, supported by GitHub Actions for CI/CD automation. System monitoring and logging rely on Prometheus, Grafana, and OpenSearch. The goal of this work is to provide a robust, scalable, and open-source communication tool that educational institutions can locally host and easily adapt to their specific needs.
Research on the Application of Kotlin Multiplatform Technology: Performance and Architectural Analysis Compared to Native Development
This paper presents research on the use of Kotlin Multiplatform technology for developing mobile applications targeting both Android and iOS platforms. The study includes performance measurements, architectural analysis, and comparative evaluation with native approaches to assess the cost-effectiveness and sustainability of this solution. Three functionally identical applications were developed: one using Kotlin Multiplatform, one natively for Android, and one natively for iOS. The findings show that while Kotlin Multiplatform may have slight drawbacks in areas such as memory usage, it offers significant benefits in development speed, maintainability, and code reusability, making it a compelling choice for projects with substantial cross-platform logic sharing.
Design and implementation of a web application for patient data management, medical appointments, and report generation
This thesis presents the design and implementation of a web application for managing patient data, scheduling medical appointments, and generating reports. The aim of the system is to improve the efficiency of healthcare institutions by digitizing scheduling processes, providing access to patient history, and automating report generation. Based on a comprehensive review of literature and an analysis of European and domestic solutions, functional and technical requirements of the system were defined. The application was developed using modern web technologies, with a focus on data security and user-friendliness. Key features include appointment scheduling, calendar-based time selection, patient history tracking, and PDF report generation. The thesis also includes testing results and a comparative analysis with existing solutions in Europe and Serbia. The conclusion emphasizes the importance of digital transformation in healthcare and suggests directions for further system development.
Development of a hand gesture recognition-based system for interaction with video games
The topic of this paper is the application of hand gesture recognition for interaction with video games, with particular emphasis on first-person shooter games and the use of light guns. The proposed system employs the MediaPipe software library for detecting hand landmark points, while gesture recognition is performed using deep learning techniques. In the final part of the paper, empirical testing was conducted across various application scenarios, and the results indicate that this approach has potential for future use in video game control systems.