Agile Requirement Engineering for Scalable Cloud Systems in Automated Vehicle Ecosystems
Armin Mokhtarian, Alexandru Kampmann, Bassam Alrifaee, Stefan Kowalewski, Bastian Lampe, Lutz Eckstein
Progress in Computing Applications, Vol. 14, No. 2, 2025.
DOI: https://doi.org/10.6025/pca/2025/14/2/90-98
Link: https://www.dline.info/pca/fulltext/v14n2/pcav14n2_4.pdf
Abstract:
The UNICARagil project aims to develop a cloud-based infrastructure supporting four types of fully automated
vehiclesâ€”autoELF, autoTAXI, autoCARGO, and autoSHUTTLEâ€”each with distinct functional requirements.
Given the projectâ€™s scale, involving over 100 developers from 15 academic chairs and 6 industrial partners,
agile requirement engineering becomes crucial. This paper introduces a structured methodology combining
agile and classical requirement engineering to accommodate evolving requirements across varied use cases. A
template-based survey was designed to gather 47 use cases, which were transformed into 42 system
requirements using a pattern-based approach that emphasizes completeness, clarity, and traceability. These
were then translated into system design components and cloud services, resulting in over 70 API endpoints.The design leveraged OpenAPI for endpoint specification, enabling automated code generation using tools like
the OpenAPI Generator and bootprint to produce Flask server stubs and documentation. A GitLab CI pipeline
ensures continuous integration by generating code and documentation upon each update. This iterative,
modular, and scalable process allows rapid prototyping and adaptability, aligning well with the projectâ€™s
dynamic development environment. The proposed methodology proves effective in managing complexity and
supporting the agile development of a cloud system for highly automated and networked vehicles.