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());

type ObjectKey [32]byte

// GenerateKey generates a unique ObjectKey from a 256 bit external key
// and a source of randomness. If random is nil the default PRNG of the
// system (crypto/rand) is used.
func GenerateKey(extKey []byte, random io.Reader) (key ObjectKey) {
	if random == nil {
		random = rand.Reader
	}
	if len(extKey) != 32 { // safety check
		logger.CriticalIf(context.Background(), errors.New("crypto: invalid key length"))

import java.math.BigInteger;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying
 * the order of magnitude of the generated values uniformly at random.
 *
 * @author Louis Wasserman
 */

    treeMultiset = TreeMultiset.create();

    Random random = new Random();

    int sizeRemaining = size;

    // TODO(kevinb): generate better test contents for multisets
    while (sizeRemaining > 0) {
      // The JVM will return interned values for small ints.
      Integer value = random.nextInt(1000) + 128;
      int count = min(random.nextInt(10) + 1, sizeRemaining);
      sizeRemaining -= count;

    sink.assertBytes(new byte[] {1, 2, 0, 0}); // padded with zeros
  }

  public void testString() {
    Random random = new Random();
    for (int i = 0; i < 100; i++) {
      byte[] bytes = new byte[64];
      random.nextBytes(bytes);
      String s = new String(bytes, UTF_16LE); // so all random strings are valid
      assertEquals(
          new Sink(4).putUnencodedChars(s).hash(),

  // 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

    }
    return new String(result);
  }

  private static String newTestString(Random random, BitSet bitSet, int percentMatching) {
    String allMatchingChars = allMatchingChars(bitSet);
    char[] result = new char[STRING_LENGTH];
    // Fill with matching chars.
    for (int i = 0; i < result.length; i++) {
      result[i] = allMatchingChars.charAt(random.nextInt(allMatchingChars.length()));
    }

    }
    return new String(result);
  }

  private static String newTestString(Random random, BitSet bitSet, int percentMatching) {
    String allMatchingChars = allMatchingChars(bitSet);
    char[] result = new char[STRING_LENGTH];
    // Fill with matching chars.
    for (int i = 0; i < result.length; i++) {
      result[i] = allMatchingChars.charAt(random.nextInt(allMatchingChars.length()));
    }

  // 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

  }

  public void testCombineOrdered_randomHashCodes() {
    Random random = new Random(7);
    List<HashCode> hashCodes = new ArrayList<>();
    for (int i = 0; i < 10; i++) {
      hashCodes.add(HashCode.fromLong(random.nextLong()));
    }
    HashCode hashCode1 = Hashing.combineOrdered(hashCodes);
    Collections.shuffle(hashCodes, random);
    HashCode hashCode2 = Hashing.combineOrdered(hashCodes);