Automating the Detection of Requirement Dependencies Using Large Language Models

Researchers developed LEREDD, an LLM-based system that automates the detection of dependencies between software requirements using Retrieval-Augmented Generation and In-Context Learning. The system achieved 93% accuracy in classifying requirement dependencies, significantly outperforming existing baselines with relative gains of over 94% in F1 scores for specific dependency types.