Showing 6 open source projects for "java class analysis"

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  • 1

    Poor Man's Timing And Profiling

    Library tools to collect timing in Java, C, C++

    A collection of library code and tools for application execution profiling and performance testing. You can create stopwatches to time select portions of your code. You can measure differences (often to sub-millisecond accuracy) between clocks on different machines. You can log application events in a .csv format for subsequent analysis. You can also generate CPU loading logs in a .csv format.
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  • 2
    A framework that compares performance of different pieces of code. Available in four languages: c#.net (SharpKinoko), java (JKinoko), c (CKinoko) and c++ (CppKinoko)
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  • 3
    Note: this tool has moved to github, this repository is not maintained any more. See https://github.com/turdusmerula/ftrace GScopeLog is a tool for instrumenting c++ code through gcc. The main purpose is to trace entry/exit point of functions. A status file may be generated to give overview of functions calls and timing informations with minimal impact on performances.
    Downloads: 1 This Week
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  • 4
    Real time micro benchmark multi-lingual suite (RTMB) provides a good way to measure the deterministic quality of hardware, an operating system, or a Java Virtual Machine. RTMB consists of benchmarks in C, C++ and Java
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  • 5
    It's a integrated performance analysis tool with GUI, which is integrated with various utilities such as strace, Gcov, Gprof, proc etc which are open released and are for analyzing performance of linux system
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  • 6

    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...
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