The OMR project consists of a highly integrated set of open source C and C++ components that can be used to build robust language runtimes that will support many different hardware and operating system platforms. These components include but are not limited to: memory management, threading, platform port (abstraction) library, diagnostic file support, monitoring support, garbage collection, and native Just In Time compilation.
The Eclipse Edje project provides a standard hardware abstraction Java API required for delivering IoT services that meet performance and memory constraints of microcontroller-based devices. Edje also provides ready-to-use software packages for target hardware that developers can get from third-parties to develop quickly and easily IoT device software and applications.
Eclipse Collections is a collections framework for Java. It has JDK-compatible List, Set and Map implementations with a rich API, additional types not found in the JDK like Bags, Multimaps and set of utility classes that work with any JDK compatible Collections, Arrays, Maps or Strings. The iteration protocol was inspired by the Smalltalk collection framework.
Project hawkBit aims to create a domain independent back end solution for rolling out software updates to constrained edge devices as well as more powerful controllers and gateways connected to IP based networking infrastructure. Devices can be connected to the hawkBit server either directly through an optimized interface or indirectly through federated device management servers.
Cloud Foundry Tools provide an extensible framework and common UI to deploy applications to different Cloud Foundry targets, and it is a framework that closely integrates with Web Tools Platform (WTP) and Eclipse. It allows application scaling and services management from the same Eclipse-based IDE where applications are developed. Applications can also be debugged on Cloud Foundry using the built-in Eclipse debugger. This makes it very convenient for developers to work on applications running on CF.
This project allows user interface to be created from beans or graphs of beans. The user interface available has standard widgets which have few dependencies to reuse. For instance there are widgets for editing numbers with bounds validation, units and that allow expressions of other boxes. There are widgets for entering a range of values and expanding out bean graphs to complete Design of Experiments work.
Visualization is a critical part of science and engineering projects and has roles in both setting up problems and post-processing results. The input or "construction" side can include things like constructing 3D geometries or volume meshes of physical space and the post-processing side can include everything from visualizing those geometries and meshes to plotting results to analyzing images to visualizing real data to almost everything else imagineable.
The APP4MC project provides a tool chain environment and de-facto standard to integrate tools for all major design steps in the multi- and many-core development phase. A basic set of tools will be available to demonstrate all the steps needed in the development process. Companies and R&D partners will benefit from the de-facto standard for tool chains and the support given by the features of the extended APP4MC tool chain platform. The platform can be easily adapted with commercial or in-house tools.
MDHT delivers a standard object-oriented alternative to proprietary development methodologies and tooling used to specify and implement most healthcare industry standards. There are three primary categories of users for MDHT tools: authors of healthcare industry interoperability standards, certification or testing authorities who validate that an Electronic Health Record (EHR) system produces XML or JSON files that comply with the standard, and software developers that implement adapters or applications that produce and consume healthcare data.
Triquetrum delivers an open platform for managing and executing scientific workflows. The goal of Triquetrum is to support a wide range of use cases, ranging from automated processes based on predefined models, to replaying ad-hoc research workflows recorded from a user's actions in a scientific workbench UI. It will allow to define and execute models from personal pipelines with a few steps to massive models with thousands of elements.