Showing 4 open source projects for "mc-wol"

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  • 1
    Library, which open xterm window if needed. Only you need is link your program with it in build time or dynamically. You can also call it:: console subsystem. Very useful for application, such as mc, which working in interactive mode.
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  • 2
    FastFlow: programming multi-core

    FastFlow: programming multi-core

    Pattern-based multi/many-core parallel programming framework

    FastFlow is a C/C++ programming framework supporting the development of pattern-based parallel programs on multi/many-core, GPUs and distributed platforms. FastFlow run-time is built upon non-blocking threads and lock-free queues. Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on...
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  • 3

    Advance-PCT-1.0

    A novel Code transformation technique to guide test input generator

    ...These additional statements along with original program supplied into test executor to improve test data. It ensures that each atomic conditions have been invoked at least once true and once false. It is done to achieve higher MC/DC, because according to the definition of MC/DC it is required to achieve 100% condition coverage, which was not possible due to short-circuit evaluation by the compiler, due to which MC/DC was low and inadequate. This code transformation technique resolves the problem. It has applied Quince-McCluskey simplification technique to resolve complexness of predicate and then applying the method of inserting empty nested if-else conditional statements.
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  • 4

    SPSens

    Stochastic parameter sensitivity analysis for chemical networks

    SPSens is a complete software package written in C that estimates parameter sensitivities for stochastic models of chemical and biochemical reaction networks using Monte Carlo (MC) stochastic simulations. It is possible to estimate sensitivities with respect to system parameters using the following algorithms: finite difference methods (crude monte carlo, common reaction path, coupled finite differences); likelihood ratio methods; and regularized pathwise derivatives. Additionally the package includes basic stochastic simulation algorithms. ...
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