// 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;

/**
 * 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
 */

import java.math.BigInteger;
import java.util.Random;

/**
 * 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
 */

    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(),

	copy(b[dst:], b[src:src+n])
	return b
}

// byteSliceBitFlip flips a random bit in a random byte in b.
func byteSliceBitFlip(m *mutator, b []byte) []byte {
	if len(b) == 0 {
		return nil
	}
	pos := m.rand(len(b))
	b[pos] ^= 1 << uint(m.rand(8))
	return b
}

// byteSliceXORByte XORs a random byte in b with a random value.
func byteSliceXORByte(m *mutator, b []byte) []byte {
	if len(b) == 0 {
		return nil

  // 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

  namespace: ns2
spec:
  hosts:
    - random-1.host.example
  # expect address to be auto allocated
  ports:
    - number: 80
      name: http
      protocol: HTTP
  resolution: DNS
---
apiVersion: networking.istio.io/v1alpha3
kind: ServiceEntry
metadata:
  name: service-dns-with-addr
  namespace: ns2
spec:
  hosts:
    - random-2.host.example
  addresses:
    - 9.9.9.9
  ports:

import java.util.LinkedList;
import java.util.Random;

@Fork(4)
@Threads(2)
@Warmup(iterations = 10)
@State(Scope.Benchmark)
public class CachedConstructorsBenchmark {

    private final static Class<?>[] CLAZZ_ARRAY = new Class<?>[]{ArrayList.class, LinkedList.class, String.class, HashMap.class};
    private final static int ARR_LEN = 1024;
    private final static Random RANDOM = new Random();

  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) {

  location: MESH_INTERNAL
  workloadSelector:
    labels:
      app: random-{{$i}}

---
{{- end }}

---
{{- range $j := until .Instances }}
apiVersion: networking.istio.io/v1alpha3
kind: WorkloadEntry
metadata:
  name: random-{{$j}}
spec:
  serviceAccount: random
  address: 10.10.10.10
  labels:
    app: random-{{mod $j $.Services}}
---