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The DSI utilities are a mishmash of classes accumulated during the last twenty years in projects developed at the DSI (Dipartimento di Scienze dell'Informazione, i.e., Information Sciences Department), now DI (Dipartimento di Informatica, i.e., Informatics Department), of the Universita` degli Studi di Milano.
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package it.unimi.dsi.util;

/*
 * DSI utilities
 *
 * Copyright (C) 2013-2019 Sebastiano Vigna
 *
 *  This library is free software; you can redistribute it and/or modify it
 *  under the terms of the GNU Lesser General Public License as published by the Free
 *  Software Foundation; either version 3 of the License, or (at your option)
 *  any later version.
 *
 *  This library is distributed in the hope that it will be useful, but
 *  WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
 *  or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public License
 *  for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with this program; if not, see .
 *
 */

import java.security.SecureRandom;
import java.util.Random;
import java.util.SplittableRandom;

import org.apache.commons.math3.random.RandomGenerator;

import it.unimi.dsi.Util;
import it.unimi.dsi.fastutil.HashCommon;
import it.unimi.dsi.logging.ProgressLogger;

/** A fast, all-purpose, rock-solid {@linkplain Random pseudorandom number generator}. It has excellent speed, a state space (256 bits) that is large enough for
 * any parallel application, and it passes all tests we are aware of.
 * In Java, it is slightly faster than a {@link XoShiRo256StarStarRandom}.
 * More information can be found at our PRNG page.
 *
 * If you need to generate just floating-point numbers, {@link XoShiRo256PlusRandom} is slightly faster. If you are tight on space,
 * you might try {@link XoRoShiRo128PlusPlusRandom}.
 *
 * 
By using the supplied {@link #jump()} method it is possible to generate non-overlapping long sequences
 * for parallel computations; {@link #longJump()} makes it possible to create several
 * starting points, each providing several non-overlapping sequences, for distributed computations. This class provides also a {@link #split()} method to support recursive parallel computations, in the spirit of
 * {@link SplittableRandom}.
 *
 * 
Note that this is not a {@linkplain SecureRandom secure generator}.
 *
 * @version 1.0
 * @see it.unimi.dsi.util
 * @see RandomGenerator
 * @see XoShiRo256PlusPlusRandomGenerator
 */


public class XoShiRo256PlusPlusRandom extends Random {
	private static final long serialVersionUID = 1L;
	/** The internal state of the algorithm. */
	private long s0, s1, s2, s3;

	/** Creates a new generator seeded using {@link Util#randomSeed()}. */
	public XoShiRo256PlusPlusRandom() {
		this(Util.randomSeed());
	}

	/** Creates a new generator using a given seed.
	 *
	 * @param seed a seed for the generator.
	 */
	public XoShiRo256PlusPlusRandom(final long seed) {
		setSeed(seed);
	}

	@Override
	public long nextLong() {
		final long t0 = s0;
		final long result = Long.rotateLeft(t0 + s3, 23) + t0;

		final long t = s1 << 17;

		s2 ^= t0;
		s3 ^= s1;
		s1 ^= s2;
		s0 ^= s3;

		s2 ^= t;

		s3 = Long.rotateLeft(s3, 45);

		return result;
	}

	@Override
	public int nextInt() {
		return (int)nextLong();
	}

	@Override
	public int nextInt(final int n) {
		return (int)nextLong(n);
	}

	/** Returns a pseudorandom uniformly distributed {@code long} value
     * between 0 (inclusive) and the specified value (exclusive), drawn from
     * this random number generator's sequence. The algorithm used to generate
     * the value guarantees that the result is uniform, provided that the
     * sequence of 64-bit values produced by this generator is.
     *
     * @param n the positive bound on the random number to be returned.
     * @return the next pseudorandom {@code long} value between {@code 0} (inclusive) and {@code n} (exclusive).
     */
	public long nextLong(final long n) {
		if (n <= 0) throw new IllegalArgumentException("illegal bound " + n + " (must be positive)");
		long t = nextLong();
		final long nMinus1 = n - 1;
		// Rejection-based algorithm to get uniform integers in the general case
		for (long u = t >>> 1; u + nMinus1 - (t = u % n) < 0; u = nextLong() >>> 1);
		return t;
	}

	@Override
	public double nextDouble() {
		return (nextLong() >>> 11) * 0x1.0p-53;
	}

    /**
     * Returns the next pseudorandom, uniformly distributed
     * {@code double} value between {@code 0.0} and
     * {@code 1.0} from this random number generator's sequence,
     * using a fast multiplication-free method which, however,
     * can provide only 52 significant bits.
     *
     * 
This method is faster than {@link #nextDouble()}, but it
     * can return only dyadic rationals of the form k / 2⁻⁵²,
     * instead of the standard k / 2⁻⁵³. Before
     * version 2.4.1, this was actually the standard implementation of
     * {@link #nextDouble()}, so you can use this method if you need to
     * reproduce exactly results obtained using previous versions.
     *
     * 
The only difference between the output of this method and that of
     * {@link #nextDouble()} is an additional least significant bit set in half of the
     * returned values. For most applications, this difference is negligible.
     *
     * @return the next pseudorandom, uniformly distributed {@code double}
     * value between {@code 0.0} and {@code 1.0} from this
     * random number generator's sequence, using 52 significant bits only.
	 */
	public double nextDoubleFast() {
		return Double.longBitsToDouble(0x3FFL << 52 | nextLong() >>> 12) - 1.0;
	}

	@Override
	public float nextFloat() {
		return (nextLong() >>> 40) * 0x1.0p-24f;
	}

	@Override
	public boolean nextBoolean() {
		return nextLong() < 0;
	}

	@Override
	public void nextBytes(final byte[] bytes) {
		int i = bytes.length, n = 0;
		while(i != 0) {
			n = Math.min(i, 8);
			for (long bits = nextLong(); n-- != 0; bits >>= 8) bytes[--i] = (byte)bits;
		}
	}

	private static final long JUMP[] = { 0x180ec6d33cfd0abaL, 0xd5a61266f0c9392cL, 0xa9582618e03fc9aaL, 0x39abdc4529b1661cL };

	private XoShiRo256PlusPlusRandom jump(final long[] jump) {
		long s0 = 0;
		long s1 = 0;
		long s2 = 0;
		long s3 = 0;
		for(int i = 0; i < jump.length; i++)
			for(int b = 0; b < 64; b++) {
				if ((jump[i] & 1L << b) != 0) {
					s0 ^= this.s0;
					s1 ^= this.s1;
					s2 ^= this.s2;
					s3 ^= this.s3;
				}
				nextLong();
			}

		this.s0 = s0;
		this.s1 = s1;
		this.s2 = s2;
		this.s3 = s3;
		return this;
	}

	/** The jump function for this generator. It is equivalent to 2¹²⁸
	 * calls to {@link #nextLong()}; it can be used to generate 2¹²⁸
	 * non-overlapping subsequences for parallel computations.
	 *
	 * @return this generator.
	 * @see #copy()
	 */

	public XoShiRo256PlusPlusRandom jump() {
		return jump(JUMP);
	}

	private static final long LONG_JUMP[] = { 0x76e15d3efefdcbbfL, 0xc5004e441c522fb3L, 0x77710069854ee241L, 0x39109bb02acbe635L };

	/** The long-jump function for this generator. It is equivalent to 2¹⁹²
	 * calls to {@link #nextLong()}; it can be used to generate 2⁶⁴ starting points,
	 * from each of which {@link #jump()} will generate 2⁶⁴ non-overlapping
	 * subsequences for parallel distributed computations.
	 *
	 * @return this generator.
	 * @see #copy()
	 */

	public XoShiRo256PlusPlusRandom longJump() {
		return jump(LONG_JUMP);
	}

	/**
     * Returns a new instance that shares no mutable state
     * with this instance. The sequence generated by the new instance
     * depends deterministically from the state of this instance,
     * but the probability that the sequence generated by this
     * instance and by the new instance overlap is negligible.
     *
     * @return the new instance.
     */
	public XoShiRo256PlusPlusRandom split() {
		final XoShiRo256PlusPlusRandom split = new XoShiRo256PlusPlusRandom();
		split.s0 = HashCommon.murmurHash3(s0);
		split.s1 = HashCommon.murmurHash3(s1);
		split.s2 = HashCommon.murmurHash3(s2);
		split.s3 = HashCommon.murmurHash3(s3);
		return split;
	}

	/** Sets the seed of this generator.
	 *
	 * 
The argument will be used to seed a {@link SplitMix64RandomGenerator}, whose output
	 * will in turn be used to seed this generator. This approach makes “warmup” unnecessary,
	 * and makes the probability of starting from a state
	 * with a large fraction of bits set to zero astronomically small.
	 *
	 * @param seed a seed for this generator.
	 */
	@Override
	public void setSeed(final long seed) {
		final SplitMix64RandomGenerator r = new SplitMix64RandomGenerator(seed);
		s0 = r.nextLong();
		s1 = r.nextLong();
		s2 = r.nextLong();
		s3 = r.nextLong();
	}


	/** Sets the state of this generator.
	 *
	 * The internal state of the generator will be reset, and the state array filled with the provided array.
	 *
	 * @param state an array of 2 longs; at least one must be nonzero.
	 */
	public void setState(final long[] state) {
		if (state.length != 4) throw new IllegalArgumentException("The argument array contains " + state.length + " longs instead of " + 2);
		s0 = state[0];
		s1 = state[1];
		s2 = state[2];
		s3 = state[3];
	}

	public static void main(final String[] arg) {
		final long n = Long.parseLong(arg[0]);
		long x = 0;
		final ProgressLogger pl = new ProgressLogger();
		final XoShiRo256PlusPlusRandomGenerator r = new XoShiRo256PlusPlusRandomGenerator(0);
		for(int k = 10; k-- != 0;) {
			pl.start("Measuring...");
			for (long i = n; i-- != 0;)
				x ^= r.nextLong();
			pl.done(n);
			if (x == 0) System.out.println(x);
		}
	}
}