Advanced modeling techniques and methodologies for reliable and secure blockchain platforms design

This dissertation explores the transformative potential of Blockchain technology with a primary focus on its application in agri-food traceability and contributions to Software Engineering Education and Training (SEET). Conducted over three years at the Polytechnic University of Bari, this research investigates Blockchain’s capabilities to enhance transparency, security, and efficiency across various domains, with an emphasis on bridging the gap between producers and consumers within supply chains. The work is structured around two main research approaches: a comprehensive analysis of Blockchain technology and the practical development of traceability platforms. The Systematic Literature Review (SLR) conducted as part of this research identifies the primary challenges for Blockchain application in agri-food traceability, including security, architectural design, and the integration of supporting technologies. These insights form the foundation for the proposed traceability models, which reinforce trust between consumers and producers. In addressing Blockchain’s technical challenges, the research delves into quantum-safe cryptography, exploring encryption methods capable of withstanding future quantum computing threats. Additional focus areas include hybrid Blockchain architectures combining public and private models and integrating NoSQL databases to support scalable, flexible platforms. Complementary technologies such as Augmented Reality (AR) and Large Language Models (LLMs) are explored for their potential to extend Blockchain’s usability across various fields, including digital tourism. In the context of SEET, this dissertation examines methods to enhance training. The integration of gamification and the role of LLMs in peer assessment are analyzed as innovative approaches to improve educational outcomes. This focus on workforce training addresses one of the major open challenges identified in the SLR and underscores the importance of a well-prepared workforce to drive future Blockchain innovation. Finally, this dissertation outlines several key areas for future research, including decision-support tools for novice Blockchain developers, the automated generation of smart contracts through LLMs, and the integration of Blockchain in the Internet of Drones (IoD). These avenues represent the potential for expanding Blockchain’s application scope, enhancing its accessibility, and further reinforcing its role as a transformative technology across industries.