ProActive Machine Learning (PML) from Activeeon, is an open-source platform for the distribution and parallelization of machine learning (ML) workloads on any large infrastructure. It enables researchers, data scientists, developers and IT administrators to work together to design and automate ML pipelines from development to production. It manages distributed AutoML experiments, dispatches and runs parallel jobs generated by tuning algorithms to search the optimal neural architecture and/or hyperparameters. Once in production, PML allows real-time monitoring of the performance of deployed models and alerts users when an important issue is detected.

Traceability needs to be tailored to the organisation and the engineers that use it. For this purpose, it needs to integrate into existing processes, interface with existing tools, and provide a suitable structure. Eclipse Capra is an open-source traceability management tool that provides the extensibility and flexibility required to fit into a specific environment. In this talk, I will present how Eclipse Capra can be used to perform common traceability activities such as change impact analysis and coverage analysis. I will also show how it can be extended to interface with the tools currently used in the development process and how it can provide structure for the traceability links by providing a custom traceability information model. The presentation will be a great introduction to anyone looking for a traceability solution that can be integrated into their existing Eclipse-based tool-chain as well as for engineers looking for a traceability management tools that fits their specific requirements. Eclipse Capra is being further developed in the scope of the ITEA3 Project Panorama - Accelerating design efficiency for automotive and aerospace systems.