arXiv:1111.1665cs.DS
De-amortizing Binary Search Trees
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Abstract
We present a general method for de-amortizing essentially any Binary Search Tree (BST) algorithm. In particular, by transforming Splay Trees, our method produces a BST that has the same asymptotic cost as Splay Trees on any access sequence while performing each search in O(log n) worst case time. By transforming Multi-Splay Trees, we obtain a BST that is O(log log n) competitive, satisfies the scanning theorem, the static optimality theorem, the static finger theorem, the working set theorem, and performs each search in O(log n) worst case time. Moreover, we prove that if there is a dynamically optimal BST algorithm, then there is a dynamically optimal BST algorithm that answers every search in O(log n) worst case time.
> Weight is a weaker condition, since you can construct a polynomial weight sequence that results in linear height. I'd like to hear more. The varieties of weight-balanced trees I'm aware of all have logarithmic height. > In general, height is the easiest thing to restrict, but…
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