4 citations · 14 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…
Engineering for a Science-Centric Experimentation Platform
Nikos Diamantopoulos, Jeffrey Wong, David Issa Mattos +4
Netflix is an internet entertainment service that routinely employs experimentation to guide strategy around product innovations. As Netflix grew, it had the opportunity to explore…