* one from the pool. We must take the pooled connection because by taking it from the pool, we've
   * fully acquired it.
   *
   * This test yields threads to force the decision of plan1 to be deliberate and not lucky. In
   * particular, we set up this sequence of events:
   *
   *  1. take plan 0
   *  3. plan 0 connects
   *  4. finish taking plan 1
   *

// TODO(kak): consider removing some of the @CanIgnoreReturnValue annotations as appropriate
@NullUnmarked
public class MonitorBasedArrayBlockingQueue<E> extends AbstractQueue<E>
    implements BlockingQueue<E> {

  // Based on revision 1.58 of ArrayBlockingQueue by Doug Lea, from
  // http://gee.cs.oswego.edu/cgi-bin/viewcvs.cgi/jsr166/src/main/java/util/concurrent/

  /** The queued items */
  final E[] items;

    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in
    [tensorflow/addons](https://github.com/tensorflow/addons) to get some
    airtime before a decision is made regarding whether they are to be migrated
    to the core.
*   As every PR requires several CPU/GPU hours of CI testing, we discourage
    submitting PRs to fix one typo, one warning,etc. We recommend fixing the

        response = spy(response);
        when(response.getHeaderStart()).thenReturn(0);

        // Write minimal SecurityDescriptor header (20 bytes)
        buffer[20] = 1; // Revision
        buffer[21] = 0; // Sbz1
        SMBUtil.writeInt2(0x8004, buffer, 22); // Control flags
        SMBUtil.writeInt4(0, buffer, 24); // Owner offset
        SMBUtil.writeInt4(0, buffer, 28); // Group offset

the CRT for private operations and because // we use constant time windowed exponentiation. On the other hand, it // requires computing a GCD of two values that are not coprime, and then // a division, both complex variable-time operations. λ, err := totient(P, Q) if err == errDivisorTooLarge { // The divisor is too large, try again with different primes. continue } if err != nil { return nil, err } e := bigmod.NewNat().SetUint(65537) d, ok := bigmod.NewNat().InverseVarTime(e, λ) if !ok { // This...

		})
		return
	}
	dsc, err := parseReplicateDecision(ctx, bucket, dobj.ReplicationState.ReplicateDecisionStr)
	if err != nil {
		replLogOnceIf(ctx, fmt.Errorf("unable to parse replication decision parameters for bucket: %s, err: %s, decision: %s",
			bucket, err, dobj.ReplicationState.ReplicateDecisionStr), dobj.ReplicationState.ReplicateDecisionStr)
		sendEvent(eventArgs{
			BucketName: bucket,
			Object: ObjectInfo{

    /**
     * Configuration property for version range resolution used metadata "nature".
     * It may contain following string values:
     * <ul>
     *     <li>"auto" - decision done based on range being resolver: if any boundary is snapshot, use "release_or_snapshot", otherwise "release"</li>
     *     <li>"release_or_snapshot" - the default</li>

  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node
  //   and we could use that to make a decision about whether or not we timed out prior to being
  //   unparked.

  @SuppressWarnings({
    "LabelledBreakTarget", // TODO(b/345814817): Maybe fix?

    ) {
      events.add(AssertionError("onReset"))
      notifyAll()
    }
  }

  companion object {
    fun roundUp(
      num: Int,
      divisor: Int,
    ): Int = (num + divisor - 1) / divisor

    val IGNORE =
      object : PushObserver {
        override fun onRequest(
          streamId: Int,
          requestHeaders: List<Header>,
        ) = false

  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node
  //   and we could use that to make a decision about whether or not we timed out prior to being
  //   unparked.

  @SuppressWarnings({
    "LabelledBreakTarget", // TODO(b/345814817): Maybe fix?