Collaborative Continuous Testing of Automotive Services (CoCo Test)
Ann-Therese Tabea Nägele, Marc Schindewolf, Eric Sax · 2025
With the increased use of information technology (IT), cars are transforming into software-defined vehicles. Software with machine learning algorithms is realizing components dedicated to automated driving. However, the established processes for development and testing cannot keep pace with the innovations in vehicle software architecture. An increasing number of IT experts are involved in system design and development to cope with the rising proportion of software in vehicles. The development team is growing and spans the mechanical, electronic, software, and machine learning domains, resulting in a heterogeneous team structure. These heterogeneous teams must overcome challenges related to collaboration during development and testing. A process is needed to test the vehicle software architecture, which is currently changing to service orientation. The testing process must be re-usable for software updates after release to maintain the vehicle software throughout the entire product life cycle. In this paper, we propose an approach where we use existing concepts from the IT domain for collaboration and continuous software testing and, where appropriate, tailor them to the automotive industry's needs, considering existing organizational structures and established standards. The approach presented is abstracted to a set of technologies that create a solution for the existing problems being as independent of the realization as possible.