// Start at 4.88 then multiply by 2*2^phi <evil cackle> - The goal is be uniform
  // yet visit a variety of "values-relative-to-the-next-power-of-2"
  @Param({"5", "30", "180", "1100", "6900", "43000", "260000"}) // "1600000", "9800000"
  private int size;

  // TODO(kevinb): look at exact (==) hits vs. equals() hits?
  @Param({"0.2", "0.8"})
  private double hitRate;

  @Param("true")
  private boolean isUserTypeFast;

  // Start at 4.88 then multiply by 2*2^phi <evil cackle> - The goal is be uniform
  // yet visit a variety of "values-relative-to-the-next-power-of-2"
  @Param({"5", "30", "180", "1100", "6900", "43000", "260000"}) // "1600000", "9800000"
  private int size;

  // TODO(kevinb): look at exact (==) hits vs. equals() hits?
  @Param({"0.2", "0.8"})
  private double hitRate;

  @Param("true")
  private boolean isUserTypeFast;

 */
public class HashFunctionBenchmark {

  // 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);

 *   <li>hashMethod: how to hash the data (using the Hashing API or the MessageDigest API).
 * </ul>
 *
 * @author Kurt Alfred Kluever
 */
public class MessageDigestAlgorithmBenchmark {
  @Param({"10", "1000", "100000", "1000000"})
  int size;

  @Param Algorithm algorithm;
  @Param HashMethod hashMethod;

  private enum HashMethod {
    MESSAGE_DIGEST_API() {
      @Override

import java.util.List;

/**
 * Benchmark for various ways to create an {@code ImmutableList}.
 *
 * @author Louis Wasserman
 */
public class ImmutableListCreationBenchmark {

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

  private static final Object OBJECT = new Object();

  @Benchmark
  int builderAdd(int reps) {
    int size = this.size;
    int dummy = 0;
    for (int rep = 0; rep < reps; rep++) {

 * @author Kurt Alfred Kluever
 */
public class HashCodeBenchmark {

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

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

  @Param WhereToDiffer whereToDiffer;

  @Param EqualsImplementation equalsImpl;

  private enum WhereToDiffer {
    ONE_PERCENT_IN,
    LAST_BYTE,
    NOT_AT_ALL;
  }

 * @author Kurt Alfred Kluever
 */
public class HashCodeBenchmark {

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

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

  @Param WhereToDiffer whereToDiffer;

  @Param EqualsImplementation equalsImpl;

  private enum WhereToDiffer {
    ONE_PERCENT_IN,
    LAST_BYTE,
    NOT_AT_ALL;
  }

      }
    };

    abstract <T> Iterable<T> view(T root, TreeTraverser<T> viewer);
  }

  private Iterable<BinaryNode> view;

  @Param Topology topology;

  @Param({"1", "100", "10000", "1000000"})
  int size;

  @Param Traversal traversal;

  @Param({"1234"})
  SpecialRandom rng;

  @BeforeExperiment
  void setUp() {

  }

  public void testAutoIncrementStep_millis() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(1, TimeUnit.MILLISECONDS);
    assertEquals(0, ticker.read());
    assertEquals(1000000, ticker.read());
    assertEquals(2000000, ticker.read());
  }

  public void testAutoIncrementStep_seconds() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(3, TimeUnit.SECONDS);
    assertEquals(0, ticker.read());

  }

  public void testAutoIncrementStep_millis() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(1, TimeUnit.MILLISECONDS);
    assertEquals(0, ticker.read());
    assertEquals(1000000, ticker.read());
    assertEquals(2000000, ticker.read());
  }

  public void testAutoIncrementStep_seconds() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(3, TimeUnit.SECONDS);
    assertEquals(0, ticker.read());