Constructing Cross-Level Traceability Links in the Automotive Domain: A Case Study

During the development of automotive systems, establishing cross-layer traceability links between system-level and component-level requirements is crucial for ensuring the consistency and integrity of system development. However, this process faces numerous challenges: there are significant semantic differences between requirements at different levels, and system-level functions often correspond to multiple component-level functions, creating complex one-to-many mapping relationships that further increase the difficulty of traceability. To address these issues, we propose a method for constructing cross-layer traceability links for automotive systems. The method first categorizes the typical mapping relationships between system-level and component-level requirements into two patterns: aggregation and cascading. Based on predefined structured requirements meta-models and prompting engineering techniques, it utilizes LLMs to perform semantic parsing and structured modeling of natural language requirements documents. Subsequently, a terminology dictionary is constructed to unify and normalize synonymous terms across layers. Additionally, a signal dependency graph of component-level requirements is built to assist in identifying semantic links and execution paths between requirements. We use a case study to demonstrate that this method shows good adaptability in dealing with issues such as terminology heterogeneity, semantic inconsistency, and structural complexity. It significantly improves the efficiency and accuracy of constructing cross-layer traceability links, providing strong support for subsequent requirements change management, system verification, and testing.