An architecture for enabling A/B experiments in automotive embedded software
This work addresses the problem of adopting continuous A/B experimentation for automotive embedded software developers, representing an incremental advancement in applying web-based techniques to the automotive domain.
The paper tackles the challenge of enabling A/B testing in automotive embedded software by presenting a novel architecture that addresses industry-specific issues, and it was validated through practical application and a case study showing relevance and applicability.
A/B experimentation is a known technique for data-driven product development and has demonstrated its value in web-facing businesses. With the digitalisation of the automotive industry, the focus in the industry is shifting towards software. For automotive embedded software to continuously improve, A/B experimentation is considered an important technique. However, the adoption of such a technique is not without challenge. In this paper, we present an architecture to enable A/B testing in automotive embedded software. The design addresses challenges that are unique to the automotive industry in a systematic fashion. Going from hypothesis to practice, our architecture was also applied in practice for running online experiments on a considerable scale. Furthermore, a case study approach was used to compare our proposal with state-of-practice in the automotive industry. We found our architecture design to be relevant and applicable in the efforts of adopting continuous A/B experiments in automotive embedded software.