//
// Run a single type test
//
void runtest(char type)
{	
	try {
		debug("SStest", "Start test <%c>", type);
		switch (type) {
		case '.':	// default
			integrity();
			break;
		case '-':
			adhoc();
			break;
		case 'a':
			acls();
			break;
		case 'A':
			authAcls();
			break;
		case 'b':
			blobs();
			break;
		case 'c':
			codeSigning();
			break;
		case 'd':
			databases();
			break;
		case 'e':
			desEncryption();
			break;
		case 'k':
			keychainAcls();
			break;
		case 'K':
			keyBlobs();
			break;
		case 's':
			signWithRSA();
			break;
		case 't':
			authorizations();
			break;
		case 'T':
			timeouts();
			break;
		default:
			error("Invalid test selection (%c)", type);
		}
		printf("** Test step complete.\n");
		debug("SStest", "End test <%c>", type);
	} catch (CssmCommonError &err) {
		error(err, "Unexpected exception");
	} catch (...) {
		error("Unexpected system exception");
	}
}
void JavaScriptDebugServer::setJavaScriptPaused(Frame* frame, bool paused)
{
    ASSERT_ARG(frame, frame);

    if (!frame->script()->isEnabled())
        return;

    frame->script()->setPaused(paused);

    if (JSDOMWindow* window = toJSDOMWindow(frame)) {
        if (paused) {
            OwnPtr<PausedTimeouts> timeouts;
            window->pauseTimeouts(timeouts);
            m_pausedTimeouts.set(frame, timeouts.release());
        } else {
            OwnPtr<PausedTimeouts> timeouts(m_pausedTimeouts.take(frame));
            window->resumeTimeouts(timeouts);
        }
    }

    setJavaScriptPaused(frame->view(), paused);
}
Example #3
0
int main (int argc, char *argv[])
{
    /*************************
     * Initialisation de MPI *
     *************************/

    boost::mpi::environment env(argc, argv, MPI_THREAD_MULTIPLE, true);
    boost::mpi::communicator world;

    /****************************
     * Il faut au moins 4 nœuds *
     ****************************/

    const size_t ALL = world.size();
    const size_t RANK = world.rank();

    /************************
     * Initialisation de EO *
     ************************/

    eoParser parser(argc, argv);
    eoState state;    // keeps all things allocated
    dim::core::State state_dim;    // keeps all things allocated

    /*****************************
     * Definition des paramètres *
     *****************************/

    bool sync = parser.createParam(bool(true), "sync", "sync", 0, "Islands Model").value();
    bool smp = parser.createParam(bool(true), "smp", "smp", 0, "Islands Model").value();
    unsigned nislands = parser.createParam(unsigned(4), "nislands", "Number of islands (see --smp)", 0, "Islands Model").value();
    // a
    double alphaP = parser.createParam(double(0.2), "alpha", "Alpha Probability", 'a', "Islands Model").value();
    double alphaF = parser.createParam(double(0.01), "alphaF", "Alpha Fitness", 'A', "Islands Model").value();
    // b
    double betaP = parser.createParam(double(0.01), "beta", "Beta Probability", 'b', "Islands Model").value();
    // d
    double probaSame = parser.createParam(double(100./(smp ? nislands : ALL)), "probaSame", "Probability for an individual to stay in the same island", 'd', "Islands Model").value();
    // I
    bool initG = parser.createParam(bool(true), "initG", "initG", 'I', "Islands Model").value();

    bool update = parser.createParam(bool(true), "update", "update", 'U', "Islands Model").value();
    bool feedback = parser.createParam(bool(true), "feedback", "feedback", 'F', "Islands Model").value();
    bool migrate = parser.createParam(bool(true), "migrate", "migrate", 'M', "Islands Model").value();
    unsigned nmigrations = parser.createParam(unsigned(1), "nmigrations", "Number of migrations to do at each generation (0=all individuals are migrated)", 0, "Islands Model").value();
    unsigned stepTimer = parser.createParam(unsigned(1000), "stepTimer", "stepTimer", 0, "Islands Model").value();
    bool deltaUpdate = parser.createParam(bool(true), "deltaUpdate", "deltaUpdate", 0, "Islands Model").value();
    bool deltaFeedback = parser.createParam(bool(true), "deltaFeedback", "deltaFeedback", 0, "Islands Model").value();
    double sensitivity = 1 / parser.createParam(double(1.), "sensitivity", "sensitivity of delta{t} (1/sensitivity)", 0, "Islands Model").value();
    std::string rewardStrategy = parser.createParam(std::string("avg"), "rewardStrategy", "Strategy of rewarding: best or avg", 0, "Islands Model").value();

    std::vector<double> rewards(smp ? nislands : ALL, 1.);
    std::vector<double> timeouts(smp ? nislands : ALL, 1.);

    for (size_t i = 0; i < (smp ? nislands : ALL); ++i)
    {
        std::ostringstream ss;
        ss << "reward" << i;
        rewards[i] = parser.createParam(double(1.), ss.str(), ss.str(), 0, "Islands Model").value();
        ss.str("");
        ss << "timeout" << i;
        timeouts[i] = parser.createParam(double(1.), ss.str(), ss.str(), 0, "Islands Model").value();
    }

    /*********************************
     * Déclaration des composants EO *
     *********************************/

    unsigned chromSize = parser.getORcreateParam(unsigned(0), "chromSize", "The length of the bitstrings", 'n',"Problem").value();
    eoInit<EOT>& init = dim::do_make::genotype(parser, state, EOT(), 0);

    eoEvalFunc<EOT>* ptEval = NULL;
    ptEval = new SimulatedEval( rewards[RANK] );
    state.storeFunctor(ptEval);

    eoEvalFuncCounter<EOT> eval(*ptEval);

    unsigned popSize = parser.getORcreateParam(unsigned(100), "popSize", "Population Size", 'P', "Evolution Engine").value();
    dim::core::Pop<EOT>& pop = dim::do_make::detail::pop(parser, state, init);

    double targetFitness = parser.getORcreateParam(double(1000), "targetFitness", "Stop when fitness reaches",'T', "Stopping criterion").value();
    unsigned maxGen = parser.getORcreateParam(unsigned(0), "maxGen", "Maximum number of generations () = none)",'G',"Stopping criterion").value();
    dim::continuator::Base<EOT>& continuator = dim::do_make::continuator<EOT>(parser, state, eval);

    dim::core::IslandData<EOT> data(smp ? nislands : -1);

    std::string monitorPrefix = parser.getORcreateParam(std::string("result"), "monitorPrefix", "Monitor prefix filenames", '\0', "Output").value();
    dim::utils::CheckPoint<EOT>& checkpoint = dim::do_make::checkpoint<EOT>(parser, state, continuator, data, 1, stepTimer);

    /**************
     * EO routine *
     **************/

    make_parallel(parser);
    make_verbose(parser);
    make_help(parser);

    if (!smp) // no smp enabled use mpi instead
    {

        /****************************************
         * Distribution des opérateurs aux iles *
         ****************************************/

        eoMonOp<EOT>* ptMon = NULL;
        if (sync)
        {
            ptMon = new DummyOp;
        }
        else
        {
            ptMon = new SimulatedOp( timeouts[RANK] );
        }
        state.storeFunctor(ptMon);

        /**********************************
         * Déclaration des composants DIM *
         **********************************/

        dim::core::ThreadsRunner< EOT > tr;

        dim::evolver::Easy<EOT> evolver( /*eval*/*ptEval, *ptMon, false );

        dim::feedbacker::Base<EOT>* ptFeedbacker = NULL;
        if (feedback)
        {
            if (sync)
            {
                ptFeedbacker = new dim::feedbacker::sync::Easy<EOT>(alphaF);
            }
            else
            {
                ptFeedbacker = new dim::feedbacker::async::Easy<EOT>(alphaF, sensitivity, deltaFeedback);
            }
        }
        else
        {
            ptFeedbacker = new dim::algo::Easy<EOT>::DummyFeedbacker();
        }
        state_dim.storeFunctor(ptFeedbacker);

        dim::vectorupdater::Base<EOT>* ptUpdater = NULL;
        if (update)
        {
            dim::vectorupdater::Reward<EOT>* ptReward = NULL;
            if (rewardStrategy == "best")
            {
                ptReward = new dim::vectorupdater::Best<EOT>(alphaP, betaP);
            }
            else
            {
                ptReward = new dim::vectorupdater::Average<EOT>(alphaP, betaP, sensitivity, sync ? false : deltaUpdate);
            }
            state_dim.storeFunctor(ptReward);

            ptUpdater = new dim::vectorupdater::Easy<EOT>(*ptReward);
        }
        else
        {
            ptUpdater = new dim::algo::Easy<EOT>::DummyVectorUpdater();
        }
        state_dim.storeFunctor(ptUpdater);

        dim::memorizer::Easy<EOT> memorizer;

        dim::migrator::Base<EOT>* ptMigrator = NULL;
        if (migrate)
        {
            if (sync)
            {
                ptMigrator = new dim::migrator::sync::Easy<EOT>();
            }
            else
            {
                ptMigrator = new dim::migrator::async::Easy<EOT>(nmigrations);
            }
        }
        else
        {
            ptMigrator = new dim::algo::Easy<EOT>::DummyMigrator();
        }
        state_dim.storeFunctor(ptMigrator);

        dim::algo::Easy<EOT> island( evolver, *ptFeedbacker, *ptUpdater, memorizer, *ptMigrator, checkpoint, monitorPrefix );

        if (!sync)
        {
            tr.addHandler(*ptFeedbacker).addHandler(*ptMigrator).add(island);
        }

        /***************
         * Rock & Roll *
         ***************/

        /******************************************************************************
         * Création de la matrice de transition et distribution aux iles des vecteurs *
         ******************************************************************************/

        dim::core::MigrationMatrix probabilities( ALL );
        dim::core::InitMatrix initmatrix( initG, probaSame );

        if ( 0 == RANK )
        {
            initmatrix( probabilities );
            std::cout << probabilities;
            data.proba = probabilities(RANK);

            for (size_t i = 1; i < ALL; ++i)
            {
                world.send( i, 100, probabilities(i) );
            }

            std::cout << "Island Model Parameters:" << std::endl
                      << "alphaP: " << alphaP << std::endl
                      << "alphaF: " << alphaF << std::endl
                      << "betaP: " << betaP << std::endl
                      << "probaSame: " << probaSame << std::endl
                      << "initG: " << initG << std::endl
                      << "update: " << update << std::endl
                      << "feedback: " << feedback << std::endl
                      << "migrate: " << migrate << std::endl
                      << "sync: " << sync << std::endl
                      << "stepTimer: " << stepTimer << std::endl
                      << "deltaUpdate: " << deltaUpdate << std::endl
                      << "deltaFeedback: " << deltaFeedback << std::endl
                      << "sensitivity: " << sensitivity << std::endl
                      << "chromSize: " << chromSize << std::endl
                      << "popSize: " << popSize << std::endl
                      << "targetFitness: " << targetFitness << std::endl
                      << "maxGen: " << maxGen << std::endl
                      ;
        }
        else
        {
            world.recv( 0, 100, data.proba );
        }

        /******************************************
         * Get the population size of all islands *
         ******************************************/

        world.barrier();
        dim::utils::print_sum(pop);

        FitnessInit fitInit;

        apply<EOT>(fitInit, pop);

        if (sync)
        {
            island( pop, data );
        }
        else
        {
            tr( pop, data );
        }

        world.abort(0);

        return 0 ;

    }

    // smp

    /**********************************
     * Déclaration des composants DIM *
     **********************************/

    dim::core::ThreadsRunner< EOT > tr;

    std::vector< dim::core::Pop<EOT> > islandPop(nislands);
    std::vector< dim::core::IslandData<EOT> > islandData(nislands);

    dim::core::MigrationMatrix probabilities( nislands );
    dim::core::InitMatrix initmatrix( initG, probaSame );

    initmatrix( probabilities );
    std::cout << probabilities;

    FitnessInit fitInit;

    for (size_t i = 0; i < nislands; ++i)
    {
        std::cout << "island " << i << std::endl;

        islandPop[i].append(popSize, init);

        apply<EOT>(fitInit, islandPop[i]);

        islandData[i] = dim::core::IslandData<EOT>(nislands, i);

        std::cout << islandData[i].size() << " " << islandData[i].rank() << std::endl;

        islandData[i].proba = probabilities(i);
        apply<EOT>(eval, islandPop[i]);

        /****************************************
         * Distribution des opérateurs aux iles *
         ****************************************/

        eoMonOp<EOT>* ptMon = NULL;
        ptMon = new SimulatedOp( timeouts[islandData[i].rank()] );
        state.storeFunctor(ptMon);

        eoEvalFunc<EOT>* __ptEval = NULL;
        __ptEval = new SimulatedEval( rewards[islandData[i].rank()] );
        state.storeFunctor(__ptEval);

        dim::evolver::Base<EOT>* ptEvolver = new dim::evolver::Easy<EOT>( /*eval*/*__ptEval, *ptMon, false );
        state_dim.storeFunctor(ptEvolver);

        dim::feedbacker::Base<EOT>* ptFeedbacker = new dim::feedbacker::smp::Easy<EOT>(islandPop, islandData, alphaF);
        state_dim.storeFunctor(ptFeedbacker);

        dim::vectorupdater::Reward<EOT>* ptReward = NULL;
        if (rewardStrategy == "best")
        {
            ptReward = new dim::vectorupdater::Best<EOT>(alphaP, betaP);
        }
        else
        {
            ptReward = new dim::vectorupdater::Average<EOT>(alphaP, betaP, sensitivity, sync ? false : deltaUpdate);
        }
        state_dim.storeFunctor(ptReward);

        dim::vectorupdater::Base<EOT>* ptUpdater = new dim::vectorupdater::Easy<EOT>(*ptReward);
        state_dim.storeFunctor(ptUpdater);

        dim::memorizer::Base<EOT>* ptMemorizer = new dim::memorizer::Easy<EOT>();
        state_dim.storeFunctor(ptMemorizer);

        dim::migrator::Base<EOT>* ptMigrator = new dim::migrator::smp::Easy<EOT>(islandPop, islandData, monitorPrefix);
        state_dim.storeFunctor(ptMigrator);

        dim::utils::CheckPoint<EOT>& checkpoint = dim::do_make::checkpoint<EOT>(parser, state, continuator, islandData[i], 1, stepTimer);

        dim::algo::Base<EOT>* ptIsland = new dim::algo::smp::Easy<EOT>( *ptEvolver, *ptFeedbacker, *ptUpdater, *ptMemorizer, *ptMigrator, checkpoint, islandPop, islandData, monitorPrefix );
        state_dim.storeFunctor(ptIsland);

        ptEvolver->size(nislands);
        ptFeedbacker->size(nislands);
        ptReward->size(nislands);
        ptUpdater->size(nislands);
        ptMemorizer->size(nislands);
        ptMigrator->size(nislands);
        ptIsland->size(nislands);

        ptEvolver->rank(i);
        ptFeedbacker->rank(i);
        ptReward->rank(i);
        ptUpdater->rank(i);
        ptMemorizer->rank(i);
        ptMigrator->rank(i);
        ptIsland->rank(i);

        tr.add(*ptIsland);
    }

    tr(pop, data);

    return 0 ;
}