Lesson 156
Splay Trees
Self-Adjusting BST
1:00A self-adjusting BST that rotates every accessed node to the root, giving O(log n) amortized performance and excellent locality for repeated or skewed access patterns.
By the end, you can
- Explain what makes a splay tree different from a plain BST.
- Identify which of the three splay cases (zig, zig-zig, zig-zag) applies given the local shape of a node, its parent, and its grandparent.
- Trace the rotation order within a zig-zig step and explain why the grandparent edge rotates first.
- Describe the full sequence of phases in a splay operation from search to root.
- Explain the amortized O(log n) bound and why a single operation can still be Θ(n).
- Define the rank function used in the potential-function analysis and explain how the cost telescopes.
- Explain the locality payoff and the working-set theorem.
- Compare splay trees to AVL and red-black trees on metadata overhead, worst-case guarantees, and suitability for cache-like workloads.
- State what static optimality means and identify the dynamic optimality conjecture as still open.
Up next in Advanced Data Structures




