Showing 358 open source projects for "framework-arduinoststm32"

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  • 1
    Some bash scripts to download and build (cross compile with e.g. ELDK) a working GUI framework for embedded linux systems. Possible combinations are: - GTK+-DirectFB - GTK+-KDrive (XServer) - LiTE (DirectFB) - wxWidgets-KDrive (XServer)
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  • 2
    Etch is a cross-platform, language- and transport-independent framework for building and consuming network services. With Etch, service development and consumption becomes no more difficult than library development and consumption.
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  • 3
    MadButterfly is a SVG based GUI framework. Application programmers can describe user interface for their application in SVG. It is supposed to be frontend of small/embedded device, or be used to develop small games.
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  • 4
    A MVC oriented client-server web framework written in C and JavaScript for Apache HTTP servers. The server executes models and the built-in template engine creates the view. The client-side is a JS API, and makes communication with the server easy.
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  • 5
    The PNMP (Petri Nets Modeling Platform) project aims at providing, in collaboration with Eclipse EMF, GMF, PNML Framework, and other future projects, a comprehensive approach to MDD for Embedded Systems on top of the Eclipse Project platform.
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  • 6

    phpkernel

    phpkernel

    Framework orientado a objeto.
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  • 7
    CQSAT is a powerful, comprehensive and extensible framework for static analysis of program source code and detection of software defects.
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  • 8

    Alchemist plugin

    Alchemist GCC/LLVM plugin for code analysis and tuning

    News: since 2015 we continue all related developments within Collective Knowledge Framework: http://github.com/ctuning/ck/wiki Alchemist plugin is a collection of plugins for GCC/LLVM for external and fine-grain code analysis and tuning. It is intended to to extract program properties for machine learning based optimization (see MILEPOST GCC); optimize programs at fine-grain level (such as unrolling, tiling, prefetching, etc); tune default optimization heuristic; gradually decompose program and detect performance or other anomalies; generate benchmarks particularly useful to train ML-based compilers. ...
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