func BenchmarkNilCheckDeep10000(b *testing.B) { benchmarkNilCheckDeep(b, 10000) }

// benchmarkNilCheckDeep is a stress test of nilcheckelim.
// It uses the worst possible input: A linear string of
// nil checks, none of which can be eliminated.
// Run with multiple depths to observe big-O behavior.
func benchmarkNilCheckDeep(b *testing.B, depth int) {
	c := testConfig(b)
	ptrType := c.config.Types.BytePtr

    }
  }

  /*
   * The maximum number of bits in a square root for which we'll precompute an explicit half power
   * of two. This can be any value, but higher values incur more class load time and linearly
   * increasing memory consumption.
   */
  @VisibleForTesting static final int SQRT2_PRECOMPUTE_THRESHOLD = 256;

  @VisibleForTesting
  static final BigInteger SQRT2_PRECOMPUTED_BITS =

    }
  }

  /*
   * The maximum number of bits in a square root for which we'll precompute an explicit half power
   * of two. This can be any value, but higher values incur more class load time and linearly
   * increasing memory consumption.
   */
  @VisibleForTesting static final int SQRT2_PRECOMPUTE_THRESHOLD = 256;

  @VisibleForTesting
  static final BigInteger SQRT2_PRECOMPUTED_BITS =

	// We think of the mutator utilization over time as the
	// box-filtered utilization function, which we call the
	// "windowed mutator utilization function". The resulting
	// function is continuous and piecewise linear (unless
	// window==0, which we handle elsewhere), where the boundaries
	// between segments occur when either edge of the window
	// encounters a change in the instantaneous mutator

  }];

  let description = [{
That is for rows we have grad for, we update var, accum and linear as follows:
accum_new = accum + grad * grad
linear += grad - (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var
quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2
var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0
accum = accum_new
  }];

  let arguments = (ins

// TODO: this could be quadratic if lots of variables are live across lots of
// basic blocks. Figure out a way to make this function (or, more precisely, the user
// of this function) require only linear size & time.
func (s *stackAllocState) computeLive(spillLive [][]ID) {
	s.live = make([][]ID, s.f.NumBlocks())
	var phis []*Value
	live := s.f.newSparseSet(s.f.NumValues())
	defer s.f.retSparseSet(live)

// This is O(N), but we expect haystack to be small;
// so small that we expect a linear search to be faster
func containsNumber(haystack []int, needle int) bool {
	for _, v := range haystack {
		if v == needle {
			return true
		}
	}
	return false
}

// This is O(N), but we expect serviceNodePorts to be small;
// so small that we expect a linear search to be faster

	//   consisting entirely of two hyphen characters ("-",
	//   decimal value 45) followed by the boundary parameter
	//   value from the Content-Type header field, optional linear
	//   whitespace, and a terminating CRLF.
	if !bytes.HasPrefix(line, r.dashBoundary) {
		return false
	}
	rest := line[len(r.dashBoundary):]
	rest = skipLWSPChar(rest)

e:i})=>i("colors"),backgroundImage:{none:"none","gradient-to-t":"linear-gradient(to top, var(--tw-gradient-stops))","gradient-to-tr":"linear-gradient(to top right, var(--tw-gradient-stops))","gradient-to-r":"linear-gradient(to right, var(--tw-gradient-stops))","gradient-to-br":"linear-gradient(to bottom right, var(--tw-gradient-stops))","gradient-to-b":"linear-gradient(to bottom, var(--tw-gradient-stops))","gradient-to-bl":"linear-gradient(to bottom left, var(--tw-gradient-stops))","gradient-to-...

		return value
	}

}

// allocateFromRange allocates an empty IP address from the range of
// IPs between the first and last address (both included), starting
// from the start address.
// TODO: this is a linear search, it can be optimized.
func (a *Allocator) allocateFromRange(iterator func() netip.Addr, svc *api.Service) (net.IP, error) {
	for {
		ip := iterator()
		if !ip.IsValid() {
			break
		}