CS 112: Data Structures Sesh Venugopal Hash Table – Part 1 Until now, we have seen that the best worst-case time for searching in a set of n keys is O(log n), attributed to binary search of a sorted array and search in an AVL tree. But why stop there? Wouldn’t it be great if […]
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AVL Tree Juan Zhai juan.zhai@rutgers.edu Insertion • InsertavalueasinaregularBSTbysearchingforits correct position. • Backtrackfromtheinsertednodeupthechainof parents, updating the balance factor of each node along the way. Stop at a node along the way if it is unbalanced and rebalance the node. – Never stop and rebalance if no node along the backtracking path is unbalanced. – Once stop
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CS 130A (Fall 2020) Programming Assignment 3 1 Project Description AVL tree is a self balancing Binary Search Tree where the height of the two child subtrees at any node can differ by at most one. In this project, you will implement a variant of AVL tree, referred as k-AVL tree. In k-AVL tree, the
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INTRODUCTION TO ALGORITHMS THIRD EDITION THOMAS H. CORMEN CHARLES E. LEISERSON RONALD L. RIVEST CLIFFORD STEIN Introduction to Algorithms Third Edition Thomas H. Cormen Charles E. Leiserson Ronald L. Rivest Clifford Stein Introduction to Algorithms Third Edition The MIT Press Cambridge, Massachusetts London, England c 2009 Massachusetts Institute of Technology All rights reserved. No part
Algorithms FOURTH EDITION This page intentionally left blank Algorithms FOURTH EDITION Robert Sedgewick and Kevin Wayne Princeton University Upper Saddle River, NJ • Boston • Indianapolis • San Francisco New York • Toronto • Montreal • London • Munich • Paris • Madrid Capetown • Sydney • Tokyo • Singapore • Mexico City Many of
COMP2012 Object-Oriented Programming and Data Structures Topic 8: AVL Trees Dr. Desmond Tsoi Department of Computer Science & Engineering The Hong Kong University of Science and Technology Hong Kong SAR, China Rm 3553, desmond@ust.hk COMP2012 (Fall 2020) 1 / 36 Motivation A binary search trees (BST) supports efficient searching if it is well balanced —
Chapter 9c: Disk Scheduling, Metadata, Records, and Pages Ed Knorr, Slides from Sept-Dec 2020 Based on: Sections 8.2 & 8.2.1 (pages 275-277) and Sections 9.3-9.32 & 9.5-9.7.2 (pages 316- 318 & 324-333, respectively) of our textbook: • Ramakrishnan, Raghu and Gehrke, Johannes. Database Management Systems. McGraw-Hill, 2003. • IBM Corporation. Db2 11 for z/OS: SQL
Chapter 10: Tree-Structured Indexes (with a Focus on B+ Trees) Ed Knorr, Slides from Fall 2020 Based on: • Sections 10.1, 10.3-10.8.4 of Ramakrishnan & Gehrke (textbook)—i.e., basically all of Chapter 10, but skip the parts about ISAM indexes. • Sections 8.1, 8.2, and 8.2.1 – Read or re-read this part of the textbook if
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