// 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

		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
		}

// For small functions, we use Braun, Buchwald, Hack, Leißa, Mallon, and Zwinkau.
// https://pp.info.uni-karlsruhe.de/uploads/publikationen/braun13cc.pdf
// For large functions, we use Sreedhar & Gao: A Linear Time Algorithm for Placing Φ-Nodes.
// http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.1979&rep=rep1&type=pdf

const smallBlocks = 500

const debugPhi = false

   * equivalently, if this inverse view contains a key that is equal to {@code value}).
   *
   * <p>Due to the property that values in a BiMap are unique, this will tend to execute in
   * faster-than-linear time.
   *
   * @param value the object to search for in the values of this BiMap
   * @return true if a mapping exists from a key to the specified value
   */
  @Override

  private static final int CUTOFF = (int) (MAX_TABLE_SIZE * DESIRED_LOAD_FACTOR);

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing
   * with linear probing in its implementation. The returned size is the smallest power of two that
   * can hold setSize elements with the desired load factor. Always returns at least setSize + 2.
   */
  @VisibleForTesting

		arch:  arch,
		cconv: cconv,
	})
}

type regSet struct {
	lo    int
	hi    int
	Rconv func(int) string
}

// Few enough architectures that a linear scan is fastest.
// Not even worth sorting.
var regSpace []regSet

/*
	Each architecture defines a register space as a unique
	integer range.

}

LogicalResult ClusteringState::VerifyDominanceProperty(
    unsigned src_root, unsigned dst_root, Operation *insertion_point) {
  // TODO(ezhulenev): Optimize this linear scan with a map lookup.
  for (auto &member : members) {
    unsigned root = FindRoot(member.root);
    if (root != src_root) continue;

    // Block arguments do not really participate in clustering, they are only

pkg unicode, var Duployan *RangeTable
pkg unicode, var Elbasan *RangeTable
pkg unicode, var Grantha *RangeTable
pkg unicode, var Khojki *RangeTable
pkg unicode, var Khudawadi *RangeTable
pkg unicode, var Linear_A *RangeTable
pkg unicode, var Mahajani *RangeTable
pkg unicode, var Manichaean *RangeTable
pkg unicode, var Mende_Kikakui *RangeTable
pkg unicode, var Modi *RangeTable
pkg unicode, var Mro *RangeTable

// "Efficient Data Structures for Tamper-Evident Logging".
// https://www.usenix.org/legacy/event/sec09/tech/full_papers/crosby.pdf

// StoredHashIndex maps the tree coordinates (level, n)
// to a dense linear ordering that can be used for hash storage.
// Hash storage implementations that store hashes in sequential
// storage can use this function to compute where to read or write
// a given hash.

	// Try to find the g that needs to be notified.
	// If it hasn't made it to the list yet we won't find it,
	// but it won't park itself once it sees the new notify number.
	//
	// This scan looks linear but essentially always stops quickly.
	// Because g's queue separately from taking numbers,
	// there may be minor reorderings in the list, but we
	// expect the g we're looking for to be near the front.