AI-Guided Evolution of Model-Based Software Systems with Structured Knowledge Representations

Modern software systems are constantly evolving, but keeping them aligned with changing needs, technologies, and environments is a growing challenge. This project explores how artificial intelligence (AI) can help manage and guide that evolution—making it easier to understand, update, and improve complex software over time.

The research focuses on building intelligent tools that can capture and organize knowledge about a software system—from its design and code to how it behaves in real-world use. By analyzing this information, AI can help identify when changes are needed, detect inconsistencies between intended design and actual implementation, and suggest improvements. The project also investigates how to visualize and explore this information, making it easier for developers and stakeholders to make informed decisions.

Recognizing that not all decisions can or should be automated, the work also examines how AI can effectively collaborate with human experts. Ultimately, this research aims to create smarter, more adaptive software systems that can evolve efficiently while maintaining reliability and performance.