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

A/B testing is gaining attention in the automotive sector as a promising tool to measure causal 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.

Automotive Software

A/B Testing

Experiment Design

Data-Driven Software Development

Author

Yuchu Liu

Volvo Cars

Testing, Requirements, Innovation and Psychology

David Issa Mattos

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Jan Bosch

Testing, Requirements, Innovation and Psychology

Helena Holmström Olsson

Malmö university

Jonn Lantz

Volvo Cars

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

300-307
9781665427050 (ISBN)

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

Subject Categories

Software Engineering

DOI

10.1109/SEAA53835.2021.00046

More information

Latest update

1/3/2024 9