// 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

    val s = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789"
    for (i in s.indices) {
      assertRoundTrip(s.substring(0, i).encodeUtf8())
    }
    val random = Random(123456789L)
    val buf = ByteArray(4096)
    random.nextBytes(buf)
    assertRoundTrip(buf.toByteString())
  }

  private fun assertRoundTrip(data: ByteString) {
    val encodeBuffer = Buffer()
    encode(data, encodeBuffer)

        }
        return root;
      }
    },
    RANDOM {
      /**
       * Generates a tree with topology selected uniformly at random from the topologies of binary
       * trees of the specified size.
       */
      @Override
      Optional<BinaryNode> createTree(int size, Random rng) {
        int[] keys = new int[size];
        for (int i = 0; i < size; i++) {

    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());

    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark
  int strongInterner(int reps) {
    Interner<String> interner = Interners.newStrongInterner();
    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark
  int stringIntern(int reps) {

    if (TF_GetCode(status) != TF_OK) {
      TF_DeleteStatus(status);
      return "";
    }
    TF_DeleteStatus(status);

    // We add a random value into `test_dir` to ensures that two consecutive
    // runs are unlikely to clash.
    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<> distribution;
    std::string rng_val = std::to_string(distribution(gen));

      nonnegative[i] = randomNonNegativeBigInteger(Long.SIZE - 1).longValue();
      longs[i] = RANDOM_SOURCE.nextLong();
      factorialArguments[i] = RANDOM_SOURCE.nextInt(30);
      binomialArguments[i][1] = RANDOM_SOURCE.nextInt(MathBenchmarking.biggestBinomials.length);
      int k = binomialArguments[i][1];
      binomialArguments[i][0] = RANDOM_SOURCE.nextInt(MathBenchmarking.biggestBinomials[k] - k) + k;
    }
  }

  @Benchmark

    }
  }

  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[] queries = new int[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    Random random = new Random();
    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) {

  // 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