* </ul>
 *
 * <p><b>Important note:</b> the primary goal of this benchmark is to ensure that varying {@code
 * whereToDiffer} produces no observable change in performance. We want to make sure that the array
 * equals implementation is *not* short-circuiting to prevent timing-based attacks. Being fast is
 * only a secondary goal.
 *
 * @author Kurt Alfred Kluever
 */
public class HashCodeBenchmark {

    checkSha1("b617318655057264e28bc0b6fb378c8ef146be00", key, data);
  }

  public void testRfc2202_hmacSha1_case2() {
    byte[] key = "Jefe".getBytes(UTF_8);
    String data = "what do ya want for nothing?";

    checkSha1("effcdf6ae5eb2fa2d27416d5f184df9c259a7c79", key, data);
  }

  public void testRfc2202_hmacSha1_case3() {
    byte[] key = fillByteArray(20, 0xaa);

 *   <li>We need to be careful about how we suppress {@code suite()} methods in {@code common.io}.
 *       The generated suite for {@code FooTest} ends up containing {@code FooTest} itself plus some
 *       other tests. We want to exclude the other tests (which Android can't handle) while
 *       continuing to run {@code FooTest} itself. This is exactly what happens with {@code

   * behavior of futures so that you can contrast the next test with it.
   */
  public void testRegularFutureInterrupted() throws ExecutionException {

    /*
     * Here's the order of events that we want.
     *
     * 1. The client thread begins to block on a get() call to a future.
     * 2. The client thread is interrupted sometime before the result would be
     *   available.

      @CheckForNull Type ownerType, Class<?> rawType, Type... arguments) {
    if (ownerType == null) {
      return newParameterizedType(rawType, arguments);
    }
    // ParameterizedTypeImpl constructor already checks, but we want to throw NPE before IAE
    checkNotNull(arguments);
    checkArgument(rawType.getEnclosingClass() != null, "Owner type for unenclosed %s", rawType);
    return new ParameterizedTypeImpl(ownerType, rawType, arguments);
  }

 * the permits issued each second steadily increases until it hits the stable rate.
 *
 * <p>As an example, imagine that we have a list of tasks to execute, but we don't want to submit
 * more than 2 per second:
 *
 * <pre>{@code
 * final RateLimiter rateLimiter = RateLimiter.create(2.0); // rate is "2 permits per second"
 * void submitTasks(List<Runnable> tasks, Executor executor) {

        return;
      }
    }
    // Execute the runnable immediately. Because of scheduling this may end up getting called before
    // some of the previously added runnables, but we're OK with that. If we want to change the
    // contract to guarantee ordering among runnables we'd have to modify the logic here to allow
    // it.
    executeListener(runnable, executor);
  }

  /**

        just a feature that seems like a sensible addition to Guava?


        Before new features get added to Guava, we really want to be sure that it's for a use case
        that actually comes up in the real world. We want to hear the real-world use case so the
        community can discuss and debate whether this feature is actually the *best* way to address

   * "1 token per second", then this will take 3 seconds. But what does it mean to serve 7 stored
   * permits? As explained above, there is no unique answer. If we are primarily interested to deal
   * with underutilization, then we want stored permits to be given out /faster/ than fresh ones,
   * because underutilization = free resources for the taking. If we are primarily interested to

          new Supplier<LongAddable>() {
            @Override
            public LongAddable get() {
              return new LongAdder();
            }
          };
    } catch (Throwable t) { // we really want to catch *everything*
      supplier =
          new Supplier<LongAddable>() {
            @Override
            public LongAddable get() {
              return new PureJavaLongAddable();
            }
          };