package com.google.common.hash;

import static java.nio.charset.StandardCharsets.UTF_8;

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

/** Benchmarks for the hashing of UTF-8 strings. */
@NullUnmarked
public class HashStringBenchmark {
  static class MaxCodePoint {
    final int value;

    /**

 * 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

 * weak references.
 *
 * <p><strong>Performance</strong>
 *
 * <p>The extra bookkeeping done by cycle detecting locks comes at some cost to performance.
 * Benchmarks (as of December 2011) show that:
 *
 * <ul>
 *   <li>for an unnested {@code lock()} and {@code unlock()}, a cycle detecting lock takes 38ns as
 *       opposed to the 24ns taken by a plain lock.

      factorials[i] = RANDOM_SOURCE.nextInt(100);
    }
  }

  @Benchmark
  long log2(int reps) {
    long tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += Double.doubleToRawLongBits(DoubleMath.log2(positiveDoubles[j]));
    }
    return tmp;
  }

  @Benchmark
  long factorial(int reps) {
    long tmp = 0;
    for (int i = 0; i < reps; i++) {

 */

package com.google.common.collect;

import com.google.caliper.Benchmark;
import com.google.errorprone.annotations.CanIgnoreReturnValue;
import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarking interners.
 *
 * @author Dimitris Andreou
 */
@NullUnmarked
public class InternersBenchmark {
  @CanIgnoreReturnValue
  @Benchmark
  int weakInterner(int reps) {

  }

  @Benchmark
  int hashString_4(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Objects.hashCode(S0, S1, S2, S3);
    }
    return dummy;
  }

  @Benchmark
  int hashString_5(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Objects.hashCode(S0, S1, S2, S3, S4);
    }
    return dummy;
  }

  @Benchmark