An architecture for enabling A/B experiments in automotive embedded software
Abstract
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.
Cite
@article{arxiv.2107.02471,
title = {An architecture for enabling A/B experiments in automotive embedded software},
author = {Yuchu Liu and Jan Bosch and Helena Holmström Olsson and Jonn Lantz},
journal= {arXiv preprint arXiv:2107.02471},
year = {2021}
}
Comments
To appear in the 45th Annual IEEE Conference on Computers, Software and Applications (COMPSAC'2021)