The Kevoree Modeling Framework Tutorial

This tutorial shortly describes some usages of the KMF API that highlight the main features of this framework. These tutorial steps can be used to pickup some code snippets and to have a concrete, apply and running set of example. For all steps, we deliver a maven project, therefore all step can be compile with a classical mvn clean install command on a terminal or your favorite IDE. We propose a plugin for the IntelliJ IDE that a great developing experience by leveraging advanced tools such as code completion and checker of our MetaModel definition file type aka .mm files.

General Kevoree-Modeling channel

Step 0: Hello World

This initial step of the KMF tutorial will help you to define an initial meta model, generate the associated code, and use the asynchronous API to create and traverse objects.

Step 1: Advanced Traversal, Query Language and the Asynchronous API

This step of the KMF tutorial will guide you through the asynchronous manipulation of models and a query language to traverse and collect data.

Step 2: Persistence Models

This step of the KMF tutorial will guide you through how to persist your data.

Step 3: Reflexive API

This step of the KMF tutorial will guide you through the reflexive manipulation of models. This tutorial demonstrates the ability to use KMF without the need for code generation.

Step 4: Time Distortion, Universe Distortion

This step of the KMF tutorial will explain the meaning of time and universe in KMF and how these concepts enable the handling of temporal data and the parallel exploration of different actions.

Step 5: Storing Signal Data with Machine Learning

This step of the KMF tutorial will demonstrate how to define simple machine learning strategies to efficiently store a large amount of signal data via a mathematical polynomial.

Step 6: Distributed and Reactive Modeling

This step of the KMF tutorial will guide you through the distributed modeling concepts of KMF.

Step 7: Isomorphic JavaScript API

This step of the tutorial explains isomorphism and how KMF provides isomorphic models for Java and JavaScript.

Step 8: Template Engine and Graph Visualisation

This step is to show how to model and use classification algorithms (Anomaly detection).

Step 9: KInfer and Advanced Machine Learning Examples

Step 10: BigData and OffHeap Models