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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.17905 |
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| _version_ | 1866913520015114240 |
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| author | Mathieu, Claire Thurston, William |
| author_facet | Mathieu, Claire Thurston, William |
| contents | Splay trees are a simple and efficient dynamic data structure, invented by Sleator and Tarjan. The basic primitive for transforming a binary tree in this scheme is a rotation. Sleator, Tarjan, and Thurston proved that the maximum rotation distance between trees with n internal nodes is exactly 2n-6 for trees with n internal nodes (where n is larger than some constant). The proof of the upper bound is easy but the proof of the lower bound, remarkably, uses sophisticated arguments based on calculating hyperbolic volumes. We give an elementary proof of the same result. The main interest of the paper lies in the method, which is new. It basically relies on a potential function argument, similar to many amortized analyses. However, the potential of a tree is not defined explicitly, but by constructing an instance of a flow problem and using the max-flow min-cut theorem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_17905 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Rotation distance using flows Mathieu, Claire Thurston, William Discrete Mathematics Data Structures and Algorithms G.2.m Splay trees are a simple and efficient dynamic data structure, invented by Sleator and Tarjan. The basic primitive for transforming a binary tree in this scheme is a rotation. Sleator, Tarjan, and Thurston proved that the maximum rotation distance between trees with n internal nodes is exactly 2n-6 for trees with n internal nodes (where n is larger than some constant). The proof of the upper bound is easy but the proof of the lower bound, remarkably, uses sophisticated arguments based on calculating hyperbolic volumes. We give an elementary proof of the same result. The main interest of the paper lies in the method, which is new. It basically relies on a potential function argument, similar to many amortized analyses. However, the potential of a tree is not defined explicitly, but by constructing an instance of a flow problem and using the max-flow min-cut theorem. |
| title | Rotation distance using flows |
| topic | Discrete Mathematics Data Structures and Algorithms G.2.m |
| url | https://arxiv.org/abs/2409.17905 |