import java.util.Map;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;

/**
 * This class provides a skeletal implementation of the {@code Cache} interface to minimize the
 * effort required to implement this interface.
 *
 * <p>To implement a cache, the programmer needs only to extend this class and provide an

import java.util.Map;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;

/**
 * This class provides a skeletal implementation of the {@code Cache} interface to minimize the
 * effort required to implement this interface.
 *
 * <p>To implement a cache, the programmer needs only to extend this class and provide an

  }

  @Override
  public int size() {
    return size;
  }

  // We're careful to put only E instances into the array in the mainline.
  // (In the backport, we don't need this suppression, but we keep it to minimize diffs.)
  @SuppressWarnings("unchecked")
  @Override
  public UnmodifiableIterator<E> iterator() {
    return asList().iterator();
  }

  @Override
  @Nullable
  Object[] internalArray() {

import java.util.concurrent.Callable;
import java.util.concurrent.ConcurrentMap;
import java.util.concurrent.ExecutionException;

/**
 * This class provides a skeletal implementation of the {@code Cache} interface to minimize the
 * effort required to implement this interface.
 *
 * <p>To implement a cache, the programmer needs only to extend this class and provide an

   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit
   * does not normally minimize that error: to do that, you should swap the roles of {@code x} and
   * {@code y}.
   *
   * <h3>Non-finite values</h3>
   *

 * represents the task. This maximizes concurrency by having each unique key mapped to a unique
 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing
 * either of these extremes, {@code Striped} allows the user to trade between required concurrency

   * #aboutToAcquire(CycleDetectingLock)} and {@link #lockStateChanged(CycleDetectingLock)}.
   */
  // This is logically a Set, but an ArrayList is used to minimize the amount
  // of allocation done on lock()/unlock().
  private static final ThreadLocal<ArrayList<LockGraphNode>> acquiredLocks =
      new ThreadLocal<ArrayList<LockGraphNode>>() {
        @Override

  //      since, after all, this class is also a reentrant mutual exclusion lock!?

  /*
   * One of the key challenges of this class is to prevent lost signals, while trying hard to
   * minimize unnecessary signals. One simple and correct algorithm is to signal some other waiter
   * with a satisfied guard (if one exists) whenever any thread occupying the monitor exits the

     * ImmutableSortedSet#orderedBy}.
     */
    /*
     * TODO(cpovirk): use Object[] instead of E[] in the mainline? (The backport is different and
     * doesn't need this suppression, but we keep it to minimize diffs.) Generally be more clear
     * about when we have an Object[] vs. a Comparable[] or other array type in internalArray? If we
     * used Object[], we might be able to optimize toArray() to use clone() sometimes. (See

    // * The element with (index == from) should be kept.
    // * Everything with (index > from) has not been checked yet.

    // Check from the end of the list backwards (minimize expected cost of
    // moving elements when remove() is called). Stop before 'from' because
    // we already know that should be kept.
    for (int n = list.size() - 1; n > from; n--) {