Set<Object> expectedValues = ImmutableSet.of(one);
    Set<Object> actualValues = ImmutableSet.copyOf(map.values());
    assertThat(actualValues).isEqualTo(expectedValues);
  }

  /** Lookups on the map view shouldn't impact the recency queue. */
  public void testAsMapRecency() {
    CacheBuilder<Object, Object> builder =
        createCacheBuilder().concurrencyLevel(1).maximumSize(SMALL_MAX_SIZE);

 * iterators that don't support {@code remove()}. Otherwise, all optional operations are supported.
 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs

import java.util.List;
import org.jspecify.annotations.Nullable;

/**
 * An immutable well-formed internet domain name, such as {@code com} or {@code foo.co.uk}. Only
 * syntactic analysis is performed; no DNS lookups or other network interactions take place. Thus
 * there is no guarantee that the domain actually exists on the internet.
 *
 * <p>One common use of this class is to determine whether a given string is likely to represent an

        queryFieldConfig.setSearchFields(fields);

        // Test field at the end (worst case for array lookup, but same for Set)
        String testField = "field999";

        // Warm up
        for (int i = 0; i < 100; i++) {
            queryCommand.isSearchField(testField);
        }

        // Measure Set-based lookup
        long startTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {

import com.google.common.collect.ImmutableList;
import java.util.List;
import org.jspecify.annotations.Nullable;

/**
 * A memory-efficient binary trie structure for public suffix lookups. The trie is stored as a
 * series of 16-bit characters in a String.
 *
 * <p>The trie data is stored in a {@link CharSequence} where each node takes 3 characters:
 *
 * <ol>

   * only the entries for {@code keys} will be returned from {@code getAll}.
   *
   * <p>This method should be overridden when bulk retrieval is significantly more efficient than
   * many individual lookups. Note that {@link LoadingCache#getAll} will defer to individual calls
   * to {@link LoadingCache#get} if this method is not overridden.
   *
   * @param keys the unique, non-null keys whose values should be loaded

   * remove()}. Otherwise, all optional operations are supported. Null row keys, columns keys, and
   * values are not supported.
   *
   * <p>Lookups by row key are often faster than lookups by column key, because the data is stored
   * in a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still

    connection.connectionListener.connectEnd(connection, route, call)

    // If we raced another call connecting to this host, coalesce the connections. This makes for
    // 3 different lookups in the connection pool!
    val pooled3 = routePlanner.planReusePooledConnection(this, routes)
    if (pooled3 != null) return pooled3.connection

    connection.withLock {
      connectionPool.put(connection)

 *
 * <p>Cache statistics are incremented according to the following rules:
 *
 * <ul>
 *   <li>When a cache lookup encounters an existing cache entry {@code hitCount} is incremented.
 *   <li>When a cache lookup first encounters a missing cache entry, a new entry is loaded.
 *       <ul>
 *         <li>After successfully loading an entry {@code missCount} and {@code loadSuccessCount}

 *
 * <p>Cache statistics are incremented according to the following rules:
 *
 * <ul>
 *   <li>When a cache lookup encounters an existing cache entry {@code hitCount} is incremented.
 *   <li>When a cache lookup first encounters a missing cache entry, a new entry is loaded.
 *       <ul>
 *         <li>After successfully loading an entry {@code missCount} and {@code loadSuccessCount}