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 * published by the Free Software Foundation.  Oracle designates this

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 * by Oracle in the LICENSE file that accompanied this code.

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 * This code 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 General Public License

 * version 2 for more details (a copy is included in the LICENSE file that

 * accompanied this code).

 *

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package java.util;

import java.io.*;

import java.util.concurrent.atomic.AtomicLong;

import java.util.function.DoubleConsumer;

import java.util.function.IntConsumer;

import java.util.function.LongConsumer;

import java.util.stream.DoubleStream;

import java.util.stream.IntStream;

import java.util.stream.LongStream;

import java.util.stream.StreamSupport;

import jdk.internal.misc.Unsafe;

/**

 * An instance of this class is used to generate a stream of

 * pseudorandom numbers. The class uses a 48-bit seed, which is

 * modified using a linear congruential formula. (See Donald Knuth,

 * <i>The Art of Computer Programming, Volume 2</i>, Section 3.2.1.)

 * <p>

 * If two instances of {@code Random} are created with the same

 * seed, and the same sequence of method calls is made for each, they

 * will generate and return identical sequences of numbers. In order to

 * guarantee this property, particular algorithms are specified for the

 * class {@code Random}. Java implementations must use all the algorithms

 * shown here for the class {@code Random}, for the sake of absolute

 * portability of Java code. However, subclasses of class {@code Random}

 * are permitted to use other algorithms, so long as they adhere to the

 * general contracts for all the methods.

 * <p>

 * The algorithms implemented by class {@code Random} use a

 * {@code protected} utility method that on each invocation can supply

 * up to 32 pseudorandomly generated bits.

 * <p>

 * Many applications will find the method {@link Math#random} simpler to use.

 *

 * <p>Instances of {@code java.util.Random} are threadsafe.

 * However, the concurrent use of the same {@code java.util.Random}

 * instance across threads may encounter contention and consequent

 * poor performance. Consider instead using

 * {@link java.util.concurrent.ThreadLocalRandom} in multithreaded

 * designs.

 *

 * <p>Instances of {@code java.util.Random} are not cryptographically

 * secure.  Consider instead using {@link java.security.SecureRandom} to

 * get a cryptographically secure pseudo-random number generator for use

 * by security-sensitive applications.

 *

 * @author  Frank Yellin

 * @since   1.0

 */

public

class Random implements java.io.Serializable {

    /** use serialVersionUID from JDK 1.1 for interoperability */

    static final long serialVersionUID = 3905348978240129619L;

    /**

     * The internal state associated with this pseudorandom number generator.

     * (The specs for the methods in this class describe the ongoing

     * computation of this value.)

     */

    private final AtomicLong seed;

    private static final long multiplier = 0x5DEECE66DL;

    private static final long addend = 0xBL;

    private static final long mask = (1L << 48) - 1;

    private static final double DOUBLE_UNIT = 0x1.0p-53; // 1.0 / (1L << 53)

    // IllegalArgumentException messages

    static final String BadBound = "bound must be positive";

    static final String BadRange = "bound must be greater than origin";

    static final String BadSize  = "size must be non-negative";

    /**

     * Creates a new random number generator. This constructor sets

     * the seed of the random number generator to a value very likely

     * to be distinct from any other invocation of this constructor.

     */

    public Random() {

        this(seedUniquifier() ^ System.nanoTime());

    }

    private static long seedUniquifier() {

        // L'Ecuyer, "Tables of Linear Congruential Generators of

        // Different Sizes and Good Lattice Structure", 1999

        for (;;) {

            long current = seedUniquifier.get();

            long next = current * 1181783497276652981L;

            if (seedUniquifier.compareAndSet(current, next))

                return next;

        }

    }

    private static final AtomicLong seedUniquifier

        = new AtomicLong(8682522807148012L);

    /**

     * Creates a new random number generator using a single {@code long} seed.

     * The seed is the initial value of the internal state of the pseudorandom

     * number generator which is maintained by method {@link #next}.

     *

     * <p>The invocation {@code new Random(seed)} is equivalent to:

     *  <pre> {@code

     * Random rnd = new Random();

     * rnd.setSeed(seed);}</pre>

     *

     * @param seed the initial seed

     * @see   #setSeed(long)

     */

    public Random(long seed) {

        if (getClass() == Random.class)

            this.seed = new AtomicLong(initialScramble(seed));

        else {

            // subclass might have overridden setSeed

            this.seed = new AtomicLong();

            setSeed(seed);

        }

    }

    private static long initialScramble(long seed) {

        return (seed ^ multiplier) & mask;

    }

    /**

     * Sets the seed of this random number generator using a single

     * {@code long} seed. The general contract of {@code setSeed} is

     * that it alters the state of this random number generator object

     * so as to be in exactly the same state as if it had just been

     * created with the argument {@code seed} as a seed. The method

     * {@code setSeed} is implemented by class {@code Random} by

     * atomically updating the seed to

     *  <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre>

     * and clearing the {@code haveNextNextGaussian} flag used by {@link

     * #nextGaussian}.

     *

     * <p>The implementation of {@code setSeed} by class {@code Random}

     * happens to use only 48 bits of the given seed. In general, however,

     * an overriding method may use all 64 bits of the {@code long}

     * argument as a seed value.

     *

     * @param seed the initial seed

     */

    public synchronized void setSeed(long seed) {

        this.seed.set(initialScramble(seed));

        haveNextNextGaussian = false;

    }

    /**

     * Generates the next pseudorandom number. Subclasses should

     * override this, as this is used by all other methods.

     *

     * <p>The general contract of {@code next} is that it returns an

     * {@code int} value and if the argument {@code bits} is between

     * {@code 1} and {@code 32} (inclusive), then that many low-order

     * bits of the returned value will be (approximately) independently

     * chosen bit values, each of which is (approximately) equally

     * likely to be {@code 0} or {@code 1}. The method {@code next} is

     * implemented by class {@code Random} by atomically updating the seed to

     *  <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre>

     * and returning

     *  <pre>{@code (int)(seed >>> (48 - bits))}.</pre>

     *

     * This is a linear congruential pseudorandom number generator, as

     * defined by D. H. Lehmer and described by Donald E. Knuth in

     * <i>The Art of Computer Programming,</i> Volume 2:

     * <i>Seminumerical Algorithms</i>, section 3.2.1.

     *

     * @param  bits random bits

     * @return the next pseudorandom value from this random number

     *         generator's sequence

     * @since  1.1

     */

    protected int next(int bits) {

        long oldseed, nextseed;

        AtomicLong seed = this.seed;

        do {

            oldseed = seed.get();

            nextseed = (oldseed * multiplier + addend) & mask;

        } while (!seed.compareAndSet(oldseed, nextseed));

        return (int)(nextseed >>> (48 - bits));

    }

    /**

     * Generates random bytes and places them into a user-supplied

     * byte array.  The number of random bytes produced is equal to

     * the length of the byte array.

     *

     * <p>The method {@code nextBytes} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public void nextBytes(byte[] bytes) {

     *   for (int i = 0; i < bytes.length; )

     *     for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);

     *          n-- > 0; rnd >>= 8)

     *       bytes[i++] = (byte)rnd;

     * }}</pre>

     *

     * @param  bytes the byte array to fill with random bytes

     * @throws NullPointerException if the byte array is null

     * @since  1.1

     */

    public void nextBytes(byte[] bytes) {

        for (int i = 0, len = bytes.length; i < len; )

            for (int rnd = nextInt(),

                     n = Math.min(len - i, Integer.SIZE/Byte.SIZE);

                 n-- > 0; rnd >>= Byte.SIZE)

                bytes[i++] = (byte)rnd;

    }

    /**

     * The form of nextLong used by LongStream Spliterators.  If

     * origin is greater than bound, acts as unbounded form of

     * nextLong, else as bounded form.

     *

     * @param origin the least value, unless greater than bound

     * @param bound the upper bound (exclusive), must not equal origin

     * @return a pseudorandom value

     */

    final long internalNextLong(long origin, long bound) {

        long r = nextLong();

        if (origin < bound) {

            long n = bound - origin, m = n - 1;

            if ((n & m) == 0L)  // power of two

                r = (r & m) + origin;

            else if (n > 0L) {  // reject over-represented candidates

                for (long u = r >>> 1;            // ensure nonnegative

                     u + m - (r = u % n) < 0L;    // rejection check

                     u = nextLong() >>> 1) // retry

                    ;

                r += origin;

            }

            else {              // range not representable as long

                while (r < origin || r >= bound)

                    r = nextLong();

            }

        }

        return r;

    }

    /**

     * The form of nextInt used by IntStream Spliterators.

     * For the unbounded case: uses nextInt().

     * For the bounded case with representable range: uses nextInt(int bound)

     * For the bounded case with unrepresentable range: uses nextInt()

     *

     * @param origin the least value, unless greater than bound

     * @param bound the upper bound (exclusive), must not equal origin

     * @return a pseudorandom value

     */

    final int internalNextInt(int origin, int bound) {

        if (origin < bound) {

            int n = bound - origin;

            if (n > 0) {

                return nextInt(n) + origin;

            }

            else {  // range not representable as int

                int r;

                do {

                    r = nextInt();

                } while (r < origin || r >= bound);

                return r;

            }

        }

        else {

            return nextInt();

        }

    }

    /**

     * The form of nextDouble used by DoubleStream Spliterators.

     *

     * @param origin the least value, unless greater than bound

     * @param bound the upper bound (exclusive), must not equal origin

     * @return a pseudorandom value

     */

    final double internalNextDouble(double origin, double bound) {

        double r = nextDouble();

        if (origin < bound) {

            r = r * (bound - origin) + origin;

            if (r >= bound) // correct for rounding

                r = Double.longBitsToDouble(Double.doubleToLongBits(bound) - 1);

        }

        return r;

    }

    /**

     * Returns the next pseudorandom, uniformly distributed {@code int}

     * value from this random number generator's sequence. The general

     * contract of {@code nextInt} is that one {@code int} value is

     * pseudorandomly generated and returned. All 2<sup>32</sup> possible

     * {@code int} values are produced with (approximately) equal probability.

     *

     * <p>The method {@code nextInt} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public int nextInt() {

     *   return next(32);

     * }}</pre>

     *

     * @return the next pseudorandom, uniformly distributed {@code int}

     *         value from this random number generator's sequence

     */

    public int nextInt() {

        return next(32);

    }

    /**

     * Returns a pseudorandom, uniformly distributed {@code int} value

     * between 0 (inclusive) and the specified value (exclusive), drawn from

     * this random number generator's sequence.  The general contract of

     * {@code nextInt} is that one {@code int} value in the specified range

     * is pseudorandomly generated and returned.  All {@code bound} possible

     * {@code int} values are produced with (approximately) equal

     * probability.  The method {@code nextInt(int bound)} is implemented by

     * class {@code Random} as if by:

     *  <pre> {@code

     * public int nextInt(int bound) {

     *   if (bound <= 0)

     *     throw new IllegalArgumentException("bound must be positive");

     *

     *   if ((bound & -bound) == bound)  // i.e., bound is a power of 2

     *     return (int)((bound * (long)next(31)) >> 31);

     *

     *   int bits, val;

     *   do {

     *       bits = next(31);

     *       val = bits % bound;

     *   } while (bits - val + (bound-1) < 0);

     *   return val;

     * }}</pre>

     *

     * <p>The hedge "approximately" is used in the foregoing description only

     * because the next method is only approximately an unbiased source of

     * independently chosen bits.  If it were a perfect source of randomly

     * chosen bits, then the algorithm shown would choose {@code int}

     * values from the stated range with perfect uniformity.

     * <p>

     * The algorithm is slightly tricky.  It rejects values that would result

     * in an uneven distribution (due to the fact that 2^31 is not divisible

     * by n). The probability of a value being rejected depends on n.  The

     * worst case is n=2^30+1, for which the probability of a reject is 1/2,

     * and the expected number of iterations before the loop terminates is 2.

     * <p>

     * The algorithm treats the case where n is a power of two specially: it

     * returns the correct number of high-order bits from the underlying

     * pseudo-random number generator.  In the absence of special treatment,

     * the correct number of <i>low-order</i> bits would be returned.  Linear

     * congruential pseudo-random number generators such as the one

     * implemented by this class are known to have short periods in the

     * sequence of values of their low-order bits.  Thus, this special case

     * greatly increases the length of the sequence of values returned by

     * successive calls to this method if n is a small power of two.

     *

     * @param bound the upper bound (exclusive).  Must be positive.

     * @return the next pseudorandom, uniformly distributed {@code int}

     *         value between zero (inclusive) and {@code bound} (exclusive)

     *         from this random number generator's sequence

     * @throws IllegalArgumentException if bound is not positive

     * @since 1.2

     */

    public int nextInt(int bound) {

        if (bound <= 0)

            throw new IllegalArgumentException(BadBound);

        int r = next(31);

        int m = bound - 1;

        if ((bound & m) == 0)  // i.e., bound is a power of 2

            r = (int)((bound * (long)r) >> 31);

        else {

            for (int u = r;

                 u - (r = u % bound) + m < 0;

                 u = next(31))

                ;

        }

        return r;

    }

    /**

     * Returns the next pseudorandom, uniformly distributed {@code long}

     * value from this random number generator's sequence. The general

     * contract of {@code nextLong} is that one {@code long} value is

     * pseudorandomly generated and returned.

     *

     * <p>The method {@code nextLong} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public long nextLong() {

     *   return ((long)next(32) << 32) + next(32);

     * }}</pre>

     *

     * Because class {@code Random} uses a seed with only 48 bits,

     * this algorithm will not return all possible {@code long} values.

     *

     * @return the next pseudorandom, uniformly distributed {@code long}

     *         value from this random number generator's sequence

     */

    public long nextLong() {

        // it's okay that the bottom word remains signed.

        return ((long)(next(32)) << 32) + next(32);

    }

    /**

     * Returns the next pseudorandom, uniformly distributed

     * {@code boolean} value from this random number generator's

     * sequence. The general contract of {@code nextBoolean} is that one

     * {@code boolean} value is pseudorandomly generated and returned.  The

     * values {@code true} and {@code false} are produced with

     * (approximately) equal probability.

     *

     * <p>The method {@code nextBoolean} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public boolean nextBoolean() {

     *   return next(1) != 0;

     * }}</pre>

     *

     * @return the next pseudorandom, uniformly distributed

     *         {@code boolean} value from this random number generator's

     *         sequence

     * @since 1.2

     */

    public boolean nextBoolean() {

        return next(1) != 0;

    }

    /**

     * Returns the next pseudorandom, uniformly distributed {@code float}

     * value between {@code 0.0} and {@code 1.0} from this random

     * number generator's sequence.

     *

     * <p>The general contract of {@code nextFloat} is that one

     * {@code float} value, chosen (approximately) uniformly from the

     * range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is

     * pseudorandomly generated and returned. All 2<sup>24</sup> possible

     * {@code float} values of the form <i>m&nbsp;x&nbsp;</i>2<sup>-24</sup>,

     * where <i>m</i> is a positive integer less than 2<sup>24</sup>, are

     * produced with (approximately) equal probability.

     *

     * <p>The method {@code nextFloat} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public float nextFloat() {

     *   return next(24) / ((float)(1 << 24));

     * }}</pre>

     *

     * <p>The hedge "approximately" is used in the foregoing description only

     * because the next method is only approximately an unbiased source of

     * independently chosen bits. If it were a perfect source of randomly

     * chosen bits, then the algorithm shown would choose {@code float}

     * values from the stated range with perfect uniformity.<p>

     * [In early versions of Java, the result was incorrectly calculated as:

     *  <pre> {@code

     *   return next(30) / ((float)(1 << 30));}</pre>

     * This might seem to be equivalent, if not better, but in fact it

     * introduced a slight nonuniformity because of the bias in the rounding

     * of floating-point numbers: it was slightly more likely that the

     * low-order bit of the significand would be 0 than that it would be 1.]

     *

     * @return the next pseudorandom, uniformly distributed {@code float}

     *         value between {@code 0.0} and {@code 1.0} from this

     *         random number generator's sequence

     */

    public float nextFloat() {

        return next(24) / ((float)(1 << 24));

    }

    /**

     * Returns the next pseudorandom, uniformly distributed

     * {@code double} value between {@code 0.0} and

     * {@code 1.0} from this random number generator's sequence.

     *

     * <p>The general contract of {@code nextDouble} is that one

     * {@code double} value, chosen (approximately) uniformly from the

     * range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is

     * pseudorandomly generated and returned.

     *

     * <p>The method {@code nextDouble} is implemented by class {@code Random}

     * as if by:

     *  <pre> {@code

     * public double nextDouble() {

     *   return (((long)next(26) << 27) + next(27))

     *     / (double)(1L << 53);

     * }}</pre>

     *

     * <p>The hedge "approximately" is used in the foregoing description only

     * because the {@code next} method is only approximately an unbiased