transferred from SVN to a CVS based repository on the servers of the Eclipse Foundation. After the release of Eclipse 3.7 Indigo in 2011, the Acceleo project has migrated to Git following the migration started by several official project of the Eclipse Foundation and since July 2011, the Acceleo source code is available on GitHub. Releases First stable release: Acceleo 1.0.0 available since 1 April 2006 Supported platforms Acceleo is written in Java and is deployed as a plugin in the Eclipse IDE. Acceleo is supported on Java 5+ based environments, on the following platforms: Linux macOS Windows XP, Windows Vista, Windows 7 The language Starting with Acceleo 3, the language used to define an Acceleo code generator is an implementation of the MOFM2T standard. This code generation language uses a template based approach. With this approach, a template is a text containing dedicated part where the text will be computed from elements provided by the inputs models. Those dedicated parts are most of the time expressions specified on the entity of the input models used to select and extract information from those models. Within Acceleo, those expression are based on the Eclipse implementation of the OCL language. Features Acceleo provides tools for code generation from EMF based models. Thanks to those tools, Acceleo allows, for example, incremental generation. Incremental generation gives people the ability to generate a piece of code and then modify the generated code and finally regenerating the code once again without losing the previous modifications. Acceleo also allows: code generation from any kind of metamodel compatible with EMF like UML 1, UML 2 and even custom metamodels (DSLs) customization of the generation with user defined templates generation of any textual language (C, Java, Python, etc.) Editor Acceleo contains a code generation modules editor with syntax highlighting, completion, real time error detection and refactoring. Debugger The Acceleo debugger gives the possibility to keep an eye on the progression of a generation. It let the user pause a generation with a break point, check the state of the variables and move step by step during a generation to identify problems. Profiler The profiler allow the user to figure out all the instructions executed during the generation, the number of time that those instructions have been executed and the time taken by each of those instructions. Profiling data are available in an EMF models after a generation launched with