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Eclipse Xsemantics is a DSL (implemented in Xtext itself) for writing type systems, reduction rules, interpreters and general relation rules for languages implemented in Xtext. A system definition in Xsemantics is a set of judgment rules which have a conclusion and a set of premises. Xsemantics then generates Java code that can be used in your Xtext-based language for scoping and validation.

Eclipse Xpect is a unit- and integration-testing framework to be used for Xtext-based languages. Test data (e.g. expectations) are embedded into programs written in the DSL under tests. Xpect itself is based on Junit; new test methods can be written in Java and are called by the Xpect framework with the test data.

Eclipse aCute provide development tools for C# and .NET Core inside the Eclipse IDE.

OpenJ9 is a high performance, enterprise calibre, flexibly licensed, openly governed cross platform Java Virtual Machine extending and augmenting the runtime technology components from the Eclipse OMR project (www.eclipse.org/omr) and OpenJDK project (openjdk.java.net).

It is highly optimized for fast startup, low memory footprint, quick ramp-up, and excellent throughput performance, both in dedicated as well as cloud deployments.

The BIG IoT project aims at igniting an IoT ecosystem by introducing an API (BIG IoT API) for interoperability and an online marketplace (BIG IoT Marketplace) for providers to offer and monetize their IoT resources (data and services) and for consumers to discover them and access them from their applications and services.

The goal of deeplearning4j is to provide a core set of components for building applications covering the whole lifecycle of building an intelligent AI product. Intelligent AI products within an enterprise often have a wider scope than just the machine learning part. The overall goal of providing a distribution is to provide an opinionated way of building deep learning applications covering the whole life cycle of building an AI product.

Picasso is a free open-source (Eclipse Public License) web application written in Python for rendering standard visualizations useful for training convolutional neural networks. Picasso ships with occlusion maps and saliency maps, two visualizations which help reveal issues that evaluation metrics like loss and accuracy might hide: for example, learning a proxy classification task.

Hybrid classical-quantum computing paradigms are posed to benefit the scientific applications that are ubiquitous within the scientific computing research community, including modeling and simulation of quantum many-body systems, applied math, and data analytics. However, developing quantum-classical hybrids that integrate quantum algorithmic statements alongside conventional programming models is an outstanding technical challenge.

Eclipse Simulation of Urban Mobility (SUMO) is a free and open traffic simulation toolsuite. SUMO allows modelling and analyzing intermodal traffic systems, including road vehicles, public transport, cargo logistics and pedestrians. Included with SUMO is a wealth of supporting tools, which handle tasks like route finding, visualization, network import and emission calculation. SUMO can be enhanced with custom models and it provides various APIs to remotely control and influence the simulation.

The Eclipse RedDeer project is an extensible framework used for development of automated SWT/Eclipse tests which interacts with application’s user interface. RedDeer provides the PageObjects API for comfortable testing of standard SWT (Buttons, Trees..), JFace (UIForms), Workbench (Views, Editors, ..) and Eclipse (Wizards, Preferences,...) components and also allows creating and extending your own components. RedDeer also provides capabilities to work with graphical editors based on GEF or Graphiti.