int[] allRequired, int requiredFrom, int requiredTo, double[] array, int from, int to) {
    // Choose the first selection to do...
    int requiredChosen = chooseNextSelection(allRequired, requiredFrom, requiredTo, from, to);
    int required = allRequired[requiredChosen];

    // ...do the first selection...
    selectInPlace(required, array, from, to);

    // ...then recursively perform the selections in the range below...

        list.subList(k, list.size()).clear();
      }
      list.trimToSize();
      return Collections.unmodifiableList(list);
    } else {
      TopKSelector<E> selector = TopKSelector.least(k, this);
      selector.offerAll(iterator);
      return selector.topK();
    }
  }

  /**
   * Returns the {@code k} greatest elements of the given iterable according to this ordering, in

      if (array[min] > array[i]) {
        min = i;
      }
    }
    return array[min];
  }

  static double select(int k, double[] array) {
    // This is basically a copy of com.google.math.Rank#select, with a small change in the method
    // signature: we make k 0-based rather than 1-based; and we drop from and to, and always work on
    // the whole array.
    int from = 0;

      if (array[min] > array[i]) {
        min = i;
      }
    }
    return array[min];
  }

  static double select(int k, double[] array) {
    // This is basically a copy of com.google.math.Rank#select, with a small change in the method
    // signature: we make k 0-based rather than 1-based; and we drop from and to, and always work on
    // the whole array.
    int from = 0;

 *
 * <p>On different platforms AggregateFutureState uses different strategies for its core
 * synchronization primitives. The strategies are all implemented as subtypes of AtomicHelper and
 * the strategy is selected in the static initializer of AggregateFutureState. This is convenient
 * and performant but introduces some testing difficulties. This test exercises the two fallback
 * strategies.
 *
 * <ul>

          root = Optional.of(new BinaryNode(rng.nextInt(), Optional.<BinaryNode>absent(), root));
        }
        return root;
      }
    },
    RANDOM {
      /**
       * Generates a tree with topology selected uniformly at random from the topologies of binary
       * trees of the specified size.
       */
      @Override
      Optional<BinaryNode> createTree(int size, Random rng) {
        int[] keys = new int[size];

  /**
   * The maximum value of an ASCII character.
   *
   * @since 9.0 (was type {@code int} before 12.0)
   */
  public static final char MAX = 127;

  /** A bit mask which selects the bit encoding ASCII character case. */
  private static final char CASE_MASK = 0x20;

  /**
   * Returns a copy of the input string in which all {@linkplain #isUpperCase(char) uppercase ASCII

    // ambiguous without the cast to Object because the boxed predicate prevents any overload from
    // being selected in phase 1
    Preconditions.checkState(boxedBoolean, "", (Object) boxedLong);

    // ternaries introduce their own problems. because of the ternary (which requires a boxing
    // operation) no overload can be selected in phase 1.  and in phase 2 it is ambiguous since it

     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to
     * ensure that completed write operations performed by other threads are noticed. For most
     * purposes, the "count" field, tracking the number of elements, serves as that volatile

import java.util.Comparator;
import java.util.Iterator;
import java.util.List;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * An accumulator that selects the "top" {@code k} elements added to it, relative to a provided
 * comparator. "Top" can mean the greatest or the lowest elements, specified in the factory used to
 * create the {@code TopKSelector} instance.
 *