Research

The DNet GT Lab conducts research on secure distributed systems, software engineering, privacy-enhancing technologies, artificial intelligence for software development, and decentralized applications.
The group focuses on building reliable, scalable, and intelligent software systems for modern distributed environments.

Current Research Themes

  • Secure and distributed software systems
  • Artificial intelligence for software engineering
  • Automated bug detection and vulnerability prediction
  • Smart contracts and decentralized applications
  • Privacy-enhancing technologies
  • Middleware and distributed data processing
  • Enterprise and industrial software engineering
  • Machine learning for web and embedded software systems

Research Projects

Projects Supervised by Bert Lagaisse

  • CODEGUARD
    Safe deployment of AI code assistants in software development

  • Bug Analysis and Debugging Support for Decentralized Applications (DApps)

  • Ecosystem Analysis and Bug Prediction for Smart Contracts

  • AI-enhanced Bug Detection and Code Generation

  • Detecting and Predicting Bugs in Embedded Software with AI
    Deep learning-based automated vulnerability detection in source code

  • Improving the Development of Web Applications with Machine Learning

  • A Unifying, Distributed Data Processing Middleware for Heterogeneous Privacy-Enhancing Techniques

  • Intelligent and Agile Engineering of Secure Distributed Software for Enterprise and Industry

Projects Co-Supervised by Bert Lagaisse

  • SODISA
    Scalable Software Development and Infrastructure for Self-sovereign Applications

  • Client-centric Replication for the Decentralized Web

Projects Supervised by Dave singelée

  • Realization of secure IoT systems
    The long-term research objective of this project is to design novel security and privacy solutions for IoT and cyber-physical (CP) systems, with a particular emphasis on system security. The research activities are organized into four research lines: - security of wireless communication networks - secure localization techniques - security lifecycle management - secure medical systems

Research Areas

The lab’s research combines techniques from:

  • Software Engineering
  • Distributed Systems
  • Artificial Intelligence
  • Cybersecurity
  • Privacy Engineering
  • Blockchain and Decentralized Systems
  • Machine Learning
  • Secure Software Development