'Splay trees' presentation slideshows

Algorithms and Data Structures

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Lecture 39: The Rolling Stones, Masters of the Balanced Tree

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CSCE 3110 Data Structures & Algorithm Analysis

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Balanced BST

Balanced BST. Balanced BSTs guarantee O(logN) performance at all times the height or left and right sub-trees are about the same simple BST are O(N) in the worst case Categories of BSTs AVL , SPLAY trees: dynamic environment optimal trees : static environment. AVL Trees.

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15-251

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Ideas on Treaps

Ideas on Treaps. Maverick Woo <pooh+@cmu.edu>. N,33. H,20. T,17. E,9. M,14. S,12. W,6. K,7. P,8. U,2. Z,4. Disclaimer. Articles of interest Raimund Seidel and Cecilia R. Aragon. Randomized search trees. Algorithmica 16 (1996), 464-497.

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15-211 Fundamental Data Structures and Algorithms

15-211 Fundamental Data Structures and Algorithms. Splay Trees. Ananda Guna February 8, 2005. Announcements. Homework 2 available! Due Monday, Feb.16, 11:59pm! More involved than hw1? Perhaps. Start early! It is very important that you go to recitations: We will discuss splaying.

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Hashing

Hashing. Goal Perform inserts, deletes, and finds in constant average time Topics Hash table, hash function, collisions Collision handling Separate chaining Open addressing: linear probing , quadratic probing , double hashing Rehashing Load factor. Tree Structures.

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Course Outline

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Lecture 20: Screw that, I want It All

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Balanced Search Trees

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CMSC 341

CMSC 341. Splay Trees. 21. 12. 32. 37. 20. 24. 40. 15. 55. 56. 77. Problems with BSTs. Because the shape of a BST is determined by the order that data is inserted, we run the risk of trees that are essentially lists. BST Sequence of Operations.

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Splay Trees

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Splay Trees

6. v. 8. 3. z. 4. Splay Trees. all the keys in the blue region are ? 20. all the keys in the yellow region are ? 20. Splay Trees are Binary Search Trees. (20,Z). note that two keys of equal value may be well-separated. BST Rules: entries stored only at internal nodes

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CMSC420: Splay Trees

CMSC420: Splay Trees. Kinga Dobolyi Based off notes by Dave Mount. What is the purpose of this class?. Data storage Speed Trees Binary search tree Expected runtime for search is O(logn) Could degenerate into a linked list O(n) AVL tree Operations are guaranteed to be O(logn)

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Introduction to SAFECode

Introduction to SAFECode. SAFECODE is a memory safety checking compiler Features static and runtime checks that try to verify that code is memory-safe Part of the SVA infrastructure http:// sva.cs.illinois.edu/ Uses LLVM compiler technology http://llvm.org Provides the basis for our work.

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Unified A ccess B ound

Unified A ccess B ound. Dictionary : Insert ( x ), Delete ( x ), Search ( x ) Comparison model. Solution 1 : Balanced search t ree Solution 2 : Unordered l inked list. O(log n ) O( n ). move-to-front. 2. 7. 4. 1. 9. 5. 3. Search (2), Search (2), Search (2).

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Unified Access Bound

Unified Access Bound. Dictionary : Insert ( x ), Delete ( x ), Search ( x ) Comparison model. Solution 1 : Balanced search tree Solution 2 : Unordered linked list. O(log n ) O( n ). move-to-front. 2. 7. 4. 1. 9. 5. 3. Search (2), Search (2), Search (2).

192 views • 7 slides