REFSQ 2025
Mon 7 - Thu 10 April 2025 Spain

This program is tentative and subject to change.

[Context and motivaton] Advancements in machine learning (ML) have impacted driving automation systems (DAS) as well as ML-based perception systems. This increased complexity leads to intensified multi-party collaboration and special needs for requirements representations.[Question(s)/Aim(s)] Well-defined requirements are essential in this safety-oriented domain, but requirements engineering (RE) for ML-enabled perception systems remains challenging. We aim to contribute to the cross-section of requirements representations, multi-party collaboration, and the need for a shared language for ML-enabled automotive perception systems development in DAS. [Method] A case study with ten experts from a major automotive original equipment manufacturer (OEM), its suppliers, and researchers is conducted, followed by a thematic analysis.[Principal idea(s)/Results] Current practices for requirements representations in this context rely on natural language, operational design domains (ODDs), and key performance indicators (KPIs). Multi-party collaboration uses formal communication, while RE for ML-enabled systems faces challenges from a lack of mature standards and causality issues.[Contribution/Conclusion] We identify previously unrecognized practical limitations in requirements representation for ML-based perception systems and multi-party collaboration. We highlight effective practices, and our findings suggest that a shared language and reference architecture could address key RE challenges.

This program is tentative and subject to change.

Tue 8 Apr

Displayed time zone: Brussels, Copenhagen, Madrid, Paris change

16:00 - 17:10
Research Track - Session R5 - Requirements Modeling IIResearch Track at C2 - Sala Actes
16:00
35m
Talk
LACE-HC: A Lightweight Attention-Based Classifier for Efficient Hierarchical Classification of Software RequirementsTechnical Paper
Research Track
Krupa Patel Bhagwan Mahavir University, Tanvi Trivedi Bhagwan Mahavir University, Unnati Shah Utica University, USA
16:35
35m
Talk
Requirements Representations in Machine Learning-based Automotive Perception Systems Development for Multi-Party CollaborationEvaluation Paper
Research Track
Hina Saeeda Chalmers University Sweden, Zuzana Rohacova Chalmers University of Technology, Oskar Jakobsson Chalmers University of Technology, Hans-Martin Heyn University of Gothenburg & Chalmers University of Technology, Eric Knauss Chalmers | University of Gothenburg, Alessia Knauss Zenseact AB, Jennifer Horkoff Chalmers and the University of Gothenburg