Infineon study reveals key gaps in automotive requirement engineering

As the automotive industry shifts toward software-defined vehicles, managing requirements has become a critical bottleneck. In a paper accepted at ASE 2026, researchers from Infineon, Nanyang Technological University, and the University of Melbourne analyzed an industrial dataset comprising 8,082 stakeholder requirements and 5,870 product requirements with full traceability links, decision outcomes, and deviation rationales. Using mixed quantitative and qualitative methods, they uncovered systematic structural and contextual differences between stakeholder-level and product-level requirements.

The study's most striking finding: refinement complexity is driven primarily by architectural scope and missing contextual information, not by how verbose or abstract the original requirement is. The team also developed a taxonomy of stakeholder-product mapping patterns, linking each pattern to a different level of refinement effort. These insights point to concrete opportunities: improving intake validation with better context enrichment, managing deviations more systematically, and building tool support that reduces rework. For automotive suppliers and OEMs racing to deliver software-defined features, the results offer a data-driven path to faster, more reusable product development.