*
   * In part because Cells are relatively large, we avoid creating
   * them until they are needed.  When there is no contention, all
   * updates are made to the base field.  Upon first contention (a
   * failed CAS on base update), the table is initialized to size 2.
   * The table size is doubled upon further contention until
   * reaching the nearest power of two greater than or equal to the

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

   *
   * In part because Cells are relatively large, we avoid creating
   * them until they are needed.  When there is no contention, all
   * updates are made to the base field.  Upon first contention (a
   * failed CAS on base update), the table is initialized to size 2.
   * The table size is doubled upon further contention until
   * reaching the nearest power of two greater than or equal to the

   *
   * In part because Cells are relatively large, we avoid creating
   * them until they are needed.  When there is no contention, all
   * updates are made to the base field.  Upon first contention (a
   * failed CAS on base update), the table is initialized to size 2.
   * The table size is doubled upon further contention until
   * reaching the nearest power of two greater than or equal to the

  protected AbstractFuture() {}

  // Gets and Timed Gets
  //
  // * Be responsive to interruption
  // * Don't create Waiter nodes if you aren't going to park, this helps reduce contention on the
  //   waiters field.
  // * Future completion is defined by when #value becomes non-null/non SetFuture
  // * Future completion can be observed if the waiters field contains a TOMBSTONE

  // Timed Get

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

  /**
   * Guides the allowed concurrency among update operations. Used as a hint for internal sizing. The
   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *

  /**
   * Guides the allowed concurrency among update operations. Used as a hint for internal sizing. The
   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to

 * <i>stripes</i>, increasing the granularity of a single lock and allowing independent operations
 * to lock different stripes and proceed concurrently, instead of creating contention for a single
 * lock.
 *
 * <p>The guarantee provided by this class is that equal keys lead to the same lock (or semaphore),
 * i.e. {@code if (key1.equals(key2))} then {@code striped.get(key1) == striped.get(key2)} (assuming