* 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.

   * cancelled without a call to {@code cancel}, such as by calling {@code
   * setFuture(cancelledFuture)}.
   *
   * <p>Beware of completing a future while holding a lock. Its listeners may do slow work or
   * acquire other locks, risking deadlocks.
   */
  @CanIgnoreReturnValue
  @Override
  public boolean cancel(boolean mayInterruptIfRunning) {
    Object localValue = value;

   * value, you should always choose it explicitly.
   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment

  final Waiter waiter = new Waiter();
  final CountDownLatch futureCancelled = new CountDownLatch(1);
  final Exception exception = new Exception();
  final Closeable mockCloseable = Mockito.mock(Closeable.class);

  @Override
  protected void tearDown() throws Exception {
    assertNoExpectedFailures();
    super.tearDown();
  }

  public void testFrom() throws Exception {

  final Waiter waiter = new Waiter();
  final CountDownLatch futureCancelled = new CountDownLatch(1);
  final Exception exception = new Exception();
  final Closeable mockCloseable = Mockito.mock(Closeable.class);

  @Override
  protected void tearDown() throws Exception {
    assertNoExpectedFailures();
    super.tearDown();
  }

  public void testFrom() throws Exception {