}

  @Override
  public boolean contains(@CheckForNull Object object) {
    if (object == null) {
      return false;
    }
    try {
      @SuppressWarnings("unchecked") // The worst case is usually CCE, which we catch.
      C c = (C) object;
      return range.contains(c);
    } catch (ClassCastException e) {
      return false;
    }
  }

  @Override

func g4[M ~map[string]S, E any, S ~[]E](m M) {}
func g5[E any, M ~map[string]S, S ~[]E](m M) {}

func _(m map[string][]byte) {
	g0(m)
	g1(m)
	g2(m)
	g3(m)
	g4(m)
	g5(m)
}

// Worst-case scenario.
// There are 10 unknown type parameters. In each iteration of
// constraint type inference we infer one more, from right to left.
// Each iteration looks repeatedly at all 11 type parameters,

		ca:             ca,
		monitoring:     newMonitoringMetrics(),
	}

	if len(features.CATrustedNodeAccounts) > 0 {
		// TODO: do we need some way to delayed readiness until this is synced? Probably
		// Worst case is we deny some requests though which are retried
		server.nodeAuthorizer = NewMulticlusterNodeAuthenticator(features.CATrustedNodeAccounts, controller)
	}
	return server, nil

  }

  @Override
  public boolean contains(@CheckForNull Object object) {
    if (object == null) {
      return false;
    }
    try {
      @SuppressWarnings("unchecked") // The worst case is usually CCE, which we catch.
      C c = (C) object;
      return range.contains(c);
    } catch (ClassCastException e) {
      return false;
    }
  }

  @Override

  // defining the frame) and that they are executed once per loop iteration.
  //
  // TODO(skyewm): the control dep will be added to all nodes in the cond graph.
  // This is at best unnecessary, and at worst may prevent different parts of
  // different loop iterations from executing in parallel.
  Scope cond_scope =
      scope.NewSubScope("cond").WithControlDependencies(inputs[0]);
  Output raw_cond_out;

			if nb == 1 {
				return 0, 0, CorruptInputError(len(src))
			}
			for i := nb; i < 5; i++ {
				// The short encoding truncated the output value.
				// We have to assume the worst case values (digit 84)
				// in order to ensure that the top bits are correct.
				v = v*85 + 84
			}
			for i := 0; i < nb-1; i++ {
				dst[ndst] = byte(v >> 24)
				v <<= 8
				ndst++
			}
		}

	//
	// Add a little more slack too if the page size is bigger than the runtime page size.
	// "big" could end up unaligned on its ends, forcing the scavenger to skip at worst
	// 2x pages.
	slack := uint64(bigBytes / 2)
	pageSize := uint64(os.Getpagesize())
	if pageSize > 8<<10 {
		slack += pageSize * 2
	}
	if slack > bigBytes {
		// We basically already checked this.

// Diff returns a nil slice (no output).
//
// Unix diff implementations typically look for a diff with
// the smallest number of lines inserted and removed,
// which can in the worst case take time quadratic in the
// number of lines in the texts. As a result, many implementations
// either can be made to run for a long time or cut off the search
// after a predetermined amount of work.
//

	// maximum heap address. We don't do this for the summary structure
	// because it's quite large and a discontiguous heap could cause a
	// lot of memory to be used. In this situation, the worst case overhead
	// is in the single-digit MiB if we map the whole thing.
	//
	// The base address of the backing store is always page-aligned,
	// because it comes from the OS, so it's sufficient to align the
	// index.

	// amortizes the cost of small object sweeping over the
	// benefit of having a full free span to allocate from. By
	// setting this to 100, we limit the space overhead to 1%.
	//
	// TODO(austin,mknyszek): This still has bad worst-case
	// throughput. For example, this could find just one free slot
	// on the 100th swept span. That limits allocation latency, but
	// still has very poor throughput. We could instead keep a