[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84844-en":3,"doc-seo-84844-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84844,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Bridging Stakeholder and Product Requirements: An Empirical Study of Requirement Engineering in the Automotive Industry","Automotive systems are shifting to software-driven, cyber-physical architectures, increasing the complexity and risk around requirement intake and refinement. Despite proposals for improving requirement quality, limited empirical evidence explains how stakeholder-level requirements are evaluated and transformed into product-level requirements in industrial practice. This study uses an Infineon dataset of 8,082 stakeholder requirements and 5,870 product requirements with traceability and deviation information. Mixed-method analyses identify structural and contextual differences, refinement factors, and mapping taxonomies, enabling actionable improvements to intake validation, deviation management, and contextual enrichment.","Bridging Stakeholder and Product Requirements: An Empirical Study of Requirement Engineering in the Automotive Industry  \nZixu Wang  \n[zixu.wang@tum.de](zixu.wang@tum.de)[ ](zixu.wang@tum.de)Technical University of Munich, Infineon Technologies AG Munich, Germany  \nShengcheng Yu∗ [shengcheng.yu@tum.de](shengcheng.yu@tum.de)[ ](shengcheng.yu@tum.de)Technical University of Munich Heilbronn, Germany  \nZhenchang Xing  \n[zhenchang.xing@data61.csiro.au](zhenchang.xing@data61.csiro.au)[ ](zhenchang.xing@data61.csiro.au)CSIRO’s Data61  \nAustralia  \nTobias Wenzel  \n[tobias.wenzel@infineon.com](tobias.wenzel@infineon.com)[ ](tobias.wenzel@infineon.com)Infineon Technologies AG Munich, Germany  \nChunyang Chen  \n[chun-yang.chen@tum.de](chun-yang.chen@tum.de)[ ](chun-yang.chen@tum.de)Technical University of Munich Heilbronn, Germany  \narXiv :2607 .05632v 1 [ cs . SE] 6 Jul 2026  \nAbstract  \nThe automotive industry’s shift toward software-driven systems has increased complexity while raising the stakes for requirement intake and refinement—critical not only for correctness and compliance, but also for development speed and systematic reuse. While prior research has proposed techniques for improving requirement quality, there is limited empirical understanding of how stakeholderlevel requirements are evaluated, refined, and transformed into product-level requirements in industrial automotive practice. This paper presents a large-scale empirical study of requirements engineering based on an industrial dataset from Infineon comprising 8,082 stakeholder requirements and 5,870 product requirements, enriched with traceability links, decision outcomes, deviation rationales, and domain references. Using a mixed-methods approach that combines quantitative analyses of requirement structures, decision distributions, and mapping patterns with qualitative analysis of rationales and referenced specifications, and software-and hardware-related artifacts, we investigate structural and contextual differences between stakeholder and product requirements, factors influencing acceptance, rejection, and approval with deviation, and the nature of stakeholder-to-product requirement refinement. The results reveal systematic differences across abstraction levels and show that refinement complexity is driven primarily by architectural scope and missing contextual information rather than linguistic verbosity. We further derive a taxonomy of stakeholder–product requirement mapping patterns and relate them to differing refinement effort. These findings provide concrete insights into industrial requirements intake and refinement practices and highlight actionable opportunities for improving intake validation, deviation  \n∗ Shengcheng Yu is the corresponding author.  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission [and/or a fee. Request permissions from permissions@acm.org](and/or a fee. Request permissions from permissions@acm.org).  \nASE’26, Munich, Germany  \n© 2026 Copyright held by the owner/author(s) . Publication rights licensed to ACM. ACM ISBN 978-x-xxxx-xxxx-x/YYYY/MM  \n[https://doi.org/XXXXXXX.XXXXXXX](https://doi.org/XXXXXXX.XXXXXXX)  \nmanagement, and tool-supported contextual enrichment to support faster and more reusable automotive product development.  \nCCS Concepts  \n• Software and its engineering → Requirements analysis.  \nKeywords  \nEmpirical Study, Requirements Engineering, Automotive Software  \nACM Reference Format:  \nZixu Wang, Shengcheng Yu, Zhenchang Xing, Tobias Wenzel, and Chuny","cbCaiunYyDun0hSS","https://ap.wps.com/l/cbCaiunYyDun0hSS","pdf",2898088,1,12,"English","en",105,"# Introduction\n## Problem background: software-driven automotive systems\n## Standards and quality assurance context\n## Study objective","[{\"question\":\"What problem does the study address in automotive requirements engineering?\",\"answer\":\"It addresses how stakeholder-level requirements are evaluated, refined, and transformed into product-level requirements in industrial automotive practice, where software-driven 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