4 citations · 10 across the 5 of their papers we have counts for
5 papers
Bayesian causal inference in automotive software engineering and online evaluation
Yuchu Liu, David Issa Mattos, Jan Bosch +2
Randomised field experiments, such as A/B testing, have long been the gold standard for evaluating software changes. In the automotive domain, running randomised field experiments…
On the Use of Causal Graphical Models for Designing Experiments in the Automotive Domain
David Issa Mattos, Yuchu Liu
Randomized field experiments are the gold standard for evaluating the impact of software changes on customers. In the online domain, randomization has been the main tool to ensure…
Bayesian propensity score matching in automotive embedded software engineering
Yuchu Liu, David Issa Mattos, Jan Bosch +2
Randomised field experiments, such as A/B testing, have long been the gold standard for evaluating the value that new software brings to customers. However, running randomised fiel…
An architecture for enabling A/B experiments in automotive embedded software
Yuchu Liu, Jan Bosch, Helena Holmström Olsson +1
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 indu…
Size matters? Or not: A/B testing with limited sample in automotive embedded software
Yuchu Liu, David Issa Mattos, Jan Bosch +2
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 t…