Size matters? or not: A/B testing with limited sample in automotive embedded software
Paper i proceeding, 2021

A/B testing is gaining attention in the automotive sector as a promising tool to measure casual effects from software changes. Different from the web-facing businesses, where A/B testing has been well-established, the automotive domain often suffers from limited eligible users to participate in online experiments. To address this shortcoming, we present a method for designing balanced control and treatment groups so that sound conclusions can be drawn from experiments with considerably small sample sizes. While the Balance Match Weighted method has been used in other domains such as medicine, this is the first paper to apply and evaluate it in the context of software development. Furthermore, we describe the Balance Match Weighted method in detail and we conduct a case study together with an automotive manufacturer to apply the group design method in a fleet of vehicles. Finally, we present our case study in the automotive software engineering domain, as well as a discussion on the benefits and limitations of the A/B group design method.

Data-Driven Software Development

A/B Testing

Automotive Software

Experiment Design


Yuchu Liu


David Issa Mattos

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Cyber Physical Systems

Jan Bosch

Testing, Requirements, Innovation and Psychology

Helena Holmström Olsson

Malmö universitet

Jonn Lantz

Volvo Cars

Proceedings - 2021 47th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2021


47th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2021
Palermo, Italy,


Mänsklig interaktion med IKT


Människa-datorinteraktion (interaktionsdesign)



Mer information

Senast uppdaterat