BST Search Time
- Includes, LowerBound, Upperbound, Insert, Put, Get, Erase
- Dominated by BST Search
- Runtime is O(h), where h = height of tree
- How does h related to n = size of tree?
- From basic theory: log n <= h < n
- Worst Cases (h = n - 1)
- Insert items in sorted order
- Insert items in reverse sorted order
- Best Cases (h = log n) - Insert in "level order"
- Random Case
- Theorem: If items are inserted in random order, h = O(log n)
- Problem: World is often not random. Data tends to be ordered, or mostly
ordered
?? Need better BST algorithms ??
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