long seed = new Random().nextLong();
    Random random = new Random(seed);
    insertRandomly(elements, q, random);
    return seed;
  }

  private static void insertRandomly(
      ArrayList<Integer> elements, MinMaxPriorityQueue<Integer> q, Random random) {
    while (!elements.isEmpty()) {
      int selectedIndex = random.nextInt(elements.size());

   * result is chosen from those possibilities uniformly at random.
   *
   * <p>Zero is treated as having log2 == 0.
   */
  static double randomDouble(int maxExponent) {
    double result = RANDOM_SOURCE.nextDouble();
    result = Math.scalb(result, RANDOM_SOURCE.nextInt(maxExponent + 1));
    return RANDOM_SOURCE.nextBoolean() ? result : -result;
  }

  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the

   * class-unloading when ThreadLocals are not removed.
   */
  static final ThreadLocal<int @Nullable []> threadHashCode = new ThreadLocal<>();

  /** Generator of new random hash codes */
  static final Random rng = new Random();

  /** Number of CPUS, to place bound on table size */
  static final int NCPU = Runtime.getRuntime().availableProcessors();

  /** Table of cells. When non-null, size is a power of 2. */

  private final SpecialRandom random;
  private final double hitRate;
  private final int size;

  private final Set<Element> valuesInSet;
  private final Element[] queries;

  CollectionBenchmarkSampleData(int size) {
    this(true, new SpecialRandom(), 1.0, size);
  }

  CollectionBenchmarkSampleData(
      boolean isUserTypeFast, SpecialRandom random, double hitRate, int size) {

  private val serverWriter =
    WebSocketWriter(
      isClient = false,
      sink = data,
      random = random,
      perMessageDeflate = false,
      noContextTakeover = false,
      minimumDeflateSize = 0L,
    )
  private val clientWriter =
    WebSocketWriter(
      isClient = true,
      sink = data,
      random = random,
      perMessageDeflate = false,
      noContextTakeover = false,
      minimumDeflateSize = 0L,

    }
  }

  private static class MutateTask implements Callable<int[]> {
    private final ConcurrentHashMultiset<String> multiset;
    private final ImmutableList<String> keys;
    private final Random random = new Random();

    private MutateTask(ConcurrentHashMultiset<String> multiset, ImmutableList<String> keys) {
      this.multiset = multiset;
      this.keys = keys;
    }

    @Override

  int factorialBound;

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      factorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      slowFactorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      binomials[i] = RANDOM_SOURCE.nextInt(factorials[i] + 1);
    }
  }

  /** Previous version of BigIntegerMath.factorial, kept for timing purposes. */

      exponent[i] = randomExponent();
      factorial[i] = RANDOM_SOURCE.nextInt(50);
      binomial[i] = RANDOM_SOURCE.nextInt(factorial[i] + 1);
      positive[i] = randomPositiveBigInteger(Integer.SIZE - 1).intValue();
      nonnegative[i] = randomNonNegativeBigInteger(Integer.SIZE - 1).intValue();
      ints[i] = RANDOM_SOURCE.nextInt();
    }
  }

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

  // Use a statically configured random instance for all of the benchmarks
  private static final Random random = new Random(42);

  @Param({"10", "1000", "100000", "1000000"})
  private int size;

  @Param HashFunctionEnum hashFunctionEnum;

  private byte[] testBytes;

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

  @Benchmark