In this paper we present the results of a feature importance analysis of a chemical sulphonation process.
In this paper, we present the results of applying machine learning methods during a chemical sulphonation process with the objective of automating the product quality analysis which currently is performed manually.
In this paper, we present a novel fault injection framework for system call invocation errors, called Phoebe.
In this paper, we present a novel approach, called POBS, to automatically improve the observability of Dockerized Java applications.
The unique feature of ChaosOrca is that it conducts experiments under production-like workload without instrumenting the application.
In this paper, we propose a novel design and implementation of a chaos engineering system in Java called CHAOSMACHINE.