Bridging Stakeholder and Product Requirements: An Empirical Study of Requirement Engineering in the Automotive Industry

2026-07-08 · Source: cs.SE updates on arXiv.org · Field: Technology & Digital — Software Development & Engineering, Robotics & Autonomous Systems, Software Quality Assurance & Standards · Depth: Advanced, extended

Summary

An empirical study, presented at the 41st IEEE/ACM International Conference on Automated Software Engineering in Munich, Germany, from October 12–16, 2026, investigates requirements engineering practices within the automotive industry. Utilizing an industrial dataset from Infineon comprising 8,082 stakeholder requirements and 5,870 product requirements, the research employs a mixed-methods approach. It analyzes how high-level stakeholder requirements are evaluated, refined, and transformed into product-level specifications. The study reveals systematic structural and linguistic differences between these requirement types, noting that refinement complexity stems primarily from architectural scope and missing contextual information, rather than textual length. Key findings include a taxonomy of stakeholder-to-product requirement mapping patterns and insights into factors influencing acceptance, rejection, and approval with deviation. This work identifies concrete opportunities to enhance intake validation, deviation management, and tool-supported contextual enrichment for faster, more reusable automotive product development.

Key takeaway

For Requirements Engineers in automotive development, prioritize early intake validation focusing on requirement source, scope, and standard alignment. Your acceptance decisions should treat "approved with deviation" as a structured outcome, explicitly modeling rationales and constraints in tools. Integrate standards and hardware specifications directly into your refinement workflows to proactively address missing contextual information, which significantly drives mapping complexity and rework.

Key insights

Refinement complexity in automotive requirements is driven by architectural scope and missing context, not linguistic verbosity.

Principles

• Requirement acceptance depends on scope and standard alignment.
• Deviation is a systematic outcome, not an exception.
• Refinement is knowledge reconstruction, not just text processing.

Method

A mixed-methods approach combined quantitative analysis of requirement structures, decision distributions, and mapping patterns with qualitative analysis of rationales and referenced specifications.

In practice

• Implement lightweight intake checks for scope and standard alignment.
• Model requirement deviations as first-class artifacts.
• Integrate standards and hardware documentation into refinement tools.

Topics

• Requirements Engineering
• Automotive Software
• Stakeholder Requirements
• Product Requirements
• ISO 26262
• Traceability Management

Best for: Research Scientist, Software Engineer, Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.SE updates on arXiv.org.