Adaptive Synthesis of Intelligent Monitoring Models for LLM-modified Information Systems: A Genetic Optimisation Approach

This study investigates adaptive synthesis of intelligent monitoring (IM) for applications modified by large language models (LLMs). A multi-objective, property-driven genetic approach with a tensor of chromosome representation is proposed to generate monitoring configurations under architectural changes. Using migration from Oracle to PostgreSQL as a controlled case, the study shows that functional equivalence can be maintained while monitoring-related properties drift, supporting adaptive archi tecture-aware monitoring over static settings.