super(checkNotNull(in));
    this.random = checkNotNull(random);
  }

  @Override
  public int read(byte[] b, int off, int len) throws IOException {
    return super.read(b, off, random.nextInt(len) + 1);
  }

        buf.append(BASE);
        final int lowTime = (int) (System.currentTimeMillis() >> 32);
        StringUtil.appendHex(buf, lowTime);
        StringUtil.appendHex(buf, RANDOM.nextInt());
        return buf.toString();
    }

    private static byte[] getAddress() {
        try {
            return InetAddress.getLocalHost().getAddress();
        } catch (final UnknownHostException ignore) {

    multisets.clear();
    for (int i = 0; i < ARRAY_SIZE; i++) {
      HashMultiset<Integer> multiset = HashMultiset.<Integer>create();
      multisets.add(multiset);
      queries[i] = random.nextInt();
      multiset.add(queries[i]);
    }
  }

  @Benchmark
  int add(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;

            List<ChannelInfo> list = new ArrayList<>(channels);
            return list.get(ThreadLocalRandom.current().nextInt(list.size()));
        }

        // Weighted random selection
        int random = ThreadLocalRandom.current().nextInt(totalWeight);
        int currentWeight = 0;

        for (ChannelInfo channel : channels) {
            currentWeight += channel.getScore();

  public void testDivideRemainderEuclideanProperty() {
    // Use a seed so that the test is deterministic:
    Random r = new Random(0L);
    for (int i = 0; i < 1000000; i++) {
      int dividend = r.nextInt();
      int divisor = r.nextInt();
      // Test that the Euclidean property is preserved:
      assertThat(
              dividend
                  - (divisor * UnsignedInts.divide(dividend, divisor)

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positiveDoubles[i] = randomPositiveDouble();
      doubles[i] = randomDouble(Long.SIZE);
      factorials[i] = RANDOM_SOURCE.nextInt(100);
    }
  }

  @Benchmark
  long log2(int reps) {
    long tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;

    for (int i = 0; i < ARRAY_SIZE; i++) {
      positive[i] = randomPositiveBigInteger(Integer.SIZE - 2).intValue();
      nonzero[i] = randomNonZeroBigInteger(Integer.SIZE - 2).intValue();
      ints[i] = RANDOM_SOURCE.nextInt();
    }
  }

  @Param({"DOWN", "UP", "FLOOR", "CEILING", "HALF_EVEN", "HALF_UP", "HALF_DOWN"})
  RoundingMode mode;

  @Benchmark
  int log2(int reps) {
    int tmp = 0;

    for (int i = 0; i < reps; i++) {
      dummy += cache.getUnchecked(nextRandomKey());
    }
    requests.addAndGet(reps);
    return dummy;
  }

  private int nextRandomKey() {
    int a = random.nextInt(max);

    /*
     * For example, if concentration=2.0, the following takes the square root of
     * the uniformly-distributed random integer, then truncates any fractional

  void setUp() {
    checkArgument(size > 0, "empty collection not supported");
    Set<Integer> set = new LinkedHashSet<>(size);

    Random random = new Random();
    while (set.size() < size) {
      set.add(random.nextInt());
    }
    List<Integer> list = new ArrayList<>(set);
    inputOrder.arrange(list);
    input = ImmutableList.copyOf(list);
  }

  @Benchmark
  int collections(int reps) {
    int dummy = 0;

    HashFunction getHashFunction() {
      return hashFn;
    }
  }

  // Use a constant seed for all of the benchmarks to ensure apples to apples comparisons.
  private static final int RANDOM_SEED = new Random().nextInt();

  private byte[] testBytes;

  @BeforeExperiment
  void setUp() {
    testBytes = new byte[size];
    new Random(RANDOM_SEED).nextBytes(testBytes);
  }

  @Benchmark