Self-adjusting trees in practice for large text collections

Splay and randomized search trees (RSTs) are self-balancing binary tree structures with little or no space overhead compared to a standard binary search tree (BST). Both trees are intended for use in applications where node accesses are skewed, for example in gathering the distinct words in a large text collection for index construction. We investigate the efficiency of these trees for such vocabulary accumulation. Surprisingly, unmodified splaying and RSTs are on average around 25% slower than using a standard binary tree. We investigate heuristics to limit splay tree reorganization costs and show their effectiveness in practice. In particular, a periodic rotation scheme improves the speed of splaying by 27%, while other proposed heuristics are less effective. We also report the performance of efficient bit-wise hashing and red– black trees for comparison. Copyright  2001 John Wiley & Sons, Ltd.