Editing Tree traversal (section)

===Breadth-first search===
Also, listed below is pseudocode for a simple [[Queue (data structure)|queue]] based level-order traversal, and will require space proportional to the maximum number of nodes at a given depth. This can be as much as half the total number of nodes. A more space-efficient approach for this type of traversal can be implemented using an [[iterative deepening depth-first search]].

 '''procedure''' levelorder(node)
     queue ← '''empty queue'''
     queue.enqueue(node)
     '''while''' '''not''' queue.isEmpty()
         node ← queue.dequeue()
         visit(node)
         '''if''' node.left ≠ '''null'''
             queue.enqueue(node.left)
         '''if''' node.right ≠ '''null'''
             queue.enqueue(node.right)

If the tree is represented by an array (first index is 0), it is sufficient iterating through all elements:

 '''procedure''' levelorder(array)
     '''for''' i '''from''' 0 '''to''' array.size
         visit(array[i])