package com.google.common.hash;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks for comparing {@link MessageDigest}s and {@link com.google.common.hash.HashFunction}s

package com.google.common.hash;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks for comparing {@link MessageDigest}s and {@link com.google.common.hash.HashFunction}s

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks against the Apache Commons Math utilities.
 *
 * <p>Note: the Apache benchmarks are not open sourced to avoid the extra dependency.
 *
 * @author Louis Wasserman
 */
@NullUnmarked

 */

package com.google.common.util.concurrent;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.lang.reflect.Constructor;
import java.util.concurrent.BlockingQueue;
import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks for {@link Monitor}.
 *
 * @author Justin T. Sampson
 */
@NullUnmarked
public class MonitorBenchmark {

 * limitations under the License.
 */

package com.google.common.math;

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

 * limitations under the License.
 */

package com.google.common.math;

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

    return x > 0 & (x & (x - 1)) == 0;
  }

  /**
   * Returns 1 if {@code x < y} as unsigned longs, and 0 otherwise. Assumes that x - y fits into a
   * signed long. The implementation is branch-free, and benchmarks suggest it is measurably faster
   * than the straightforward ternary expression.
   */
  @VisibleForTesting
  static int lessThanBranchFree(long x, long y) {
    // Returns the sign bit of x - y.

import java.util.concurrent.atomic.AtomicInteger;
import java.util.logging.Level;
import java.util.logging.Logger;
import org.jspecify.annotations.NullUnmarked;
import org.jspecify.annotations.Nullable;

/** Benchmarks for {@link ExecutionList}. */
@VmOptions({"-Xms8g", "-Xmx8g"})
@NullUnmarked
public class ExecutionListBenchmark {
  private static final int NUM_THREADS = 10; // make a param?

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;
import java.util.concurrent.ConcurrentSkipListMap;
import org.jspecify.annotations.NullUnmarked;

/**
 * Helper classes for various benchmarks.
 *
 * @author Christopher Swenson
 */
@NullUnmarked
final class BenchmarkHelpers {
  /** So far, this is the best way to test various implementations of {@link Set} subclasses. */

 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and
 * degrades more gracefully for worst-case input.
 *
 * <p>The implementation does not necessarily use a <i>stable</i> sorting algorithm; when multiple