}

    private static final byte[] DEFAULT_ADDRESS = new byte[] { (byte) 127, (byte) 0, (byte) 0, (byte) 1 };

    private static final SecureRandom RANDOM = new SecureRandom();

    private static final String BASE = StringUtil.toHex(getAddress()) + StringUtil.toHex(System.identityHashCode(RANDOM));

    /**
     * Creates a UUID.
     *
     * @return the UUID string
     */
    public static String create() {

  }

  @Test
  public void undirectedGraph() {
    testGraphMutation(GraphBuilder.undirected());
  }

  private static void testGraphMutation(GraphBuilder<? super Integer> graphBuilder) {
    Random gen = new Random(42); // Fixed seed so test results are deterministic.

    for (int trial = 0; trial < NUM_TRIALS; ++trial) {
      MutableGraph<Integer> graph = graphBuilder.allowsSelfLoops(true).build();

  // 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

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
 */

  // @Param({"4", "8", "64", "1024", "1048576", "1048577", "6710884", "6710883"})
  @Param({"4", "8", "64", "1024"})
  private int length;

  @BeforeExperiment
  void setUp() throws Exception {
    Random r = new Random();
    ba1 = new byte[length];
    r.nextBytes(ba1);
    ba2 = Arrays.copyOf(ba1, ba1.length);
    // Differ at the last element
    ba3 = Arrays.copyOf(ba1, ba1.length);
    ba4 = Arrays.copyOf(ba1, ba1.length);

    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(),

  private Queue<Integer> queue;

  private final Random random = new Random();

  @BeforeExperiment
  void setUp() {
    queue = heap.create(comparator.get());
    for (int i = 0; i < size; i++) {
      queue.add(random.nextInt());
    }
  }

  @Benchmark
  void pollAndAdd(int reps) {
    for (int i = 0; i < reps; i++) {
      // TODO(kevinb): precompute random #s?
      queue.add(queue.poll() ^ random.nextInt());

  }

  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);

  // 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

for idx in {1..10}; do
	# generate random nr of blocks
	COUNT=$((RANDOM % 100 + 100))
	# generate random content
	dd if=/dev/urandom bs=50K count="${COUNT}" of="${SRC_DIR}"/file"$idx"
done

# create small object that will be inlined into xl.meta
dd if=/dev/urandom bs=50K count=1 of="${INLINED_DIR}"/inlined