search trees software stack for the tree traversalnode references are pushed onto the stack as it moves down into the tree and the references are popped as the process backtracks listing shows the implementation of the iterator using software stack listing an iterator for the binary search tree using software stack class _bstmapiterator def __init__selfroot )create stack for use in traversing the tree self _thestack stack(we must traverse down to the node containing the smallest key during which each node along the path is pushed onto the stack self _traversetominnoderoot def __iter__self )return self returns the next item from the bst in key order def __next__self )if the stack is emptywe are done if self _thestack isempty(raise stopiteration else the top node on the stack contains the next key node self _thestack pop(key node key if this node has subtree rooted as the right childwe must find the node in that subtree that contains the smallest key againthe nodes along the path are pushed onto the stack if node right is not none self _traversetominnodenode right traverses down the subtree to find the node containing the smallest key during which the nodes along that path are pushed onto the stack def _traversetominnodeselfsubtree )if subtree is not none self _thestack pushsubtree self _traversetominnodesubtree left avl trees the binary search tree provides convenient structure for storing and searching data collections the efficiency of the searchinsertionand deletion operations depend on the height of the tree in the best casea binary tree of size has height of log nbut in the worst casethere is one node per levelresulting in height of thusit would be to our advantage to try to build binary search tree that has height log if we were constructing the tree from the complete set of search keysthis would be easy to accomplish the keys can be sorted in ascending order and then