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Starting Out with C++, 3 rd Edition
Starting Out with C++, 3 rd Edition

Lecture-search
Lecture-search

Binary Search Tree
Binary Search Tree

... 1 tempPtr = root->left 2 root->left = tempPtr->right 3 tempPtr->right = root 4 root = tempPtr 5 return end rotateRight ...
Tree-Structured Indexes
Tree-Structured Indexes

TREES
TREES

Chapter Objectives - Jacksonville University
Chapter Objectives - Jacksonville University

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16 B+ trees

lecture 8
lecture 8

IAT 800
IAT 800

Lower bound for the worst case
Lower bound for the worst case

... • The algorithm only uses the results of comparisons, not values of elements (*). • Very general – does not assume much about what type of data is being sorted. • However, other kinds of algorithms are possible! • In this model, it is reasonable to count #comparisons. • Note that the #comparisons is ...
Trees
Trees

... A tree consists of a collection of elements or nodes, with each node linked to its successors The height of a tree is the number of nodes in the longest path from the root node to a leaf node ...
Non-Linear Data Structures - Trees
Non-Linear Data Structures - Trees

... The traversals we have examined here are also depth first traversals. The traversal algorithm always descends to the greatest possible depth within the tree, before back tracking and trying an alternate path. This means that a search based on these algorithms, may traverse several alternate paths, b ...
Midterm
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CS790 – Introduction to Bioinformatics
CS790 – Introduction to Bioinformatics

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Basic Element of Data Structures like linked list, stack and queue
Basic Element of Data Structures like linked list, stack and queue

... Binary search tree • A binary search tree is a binary tree. It may be empty. If not empty, then it satisfies the following property. 1. Every element has a key and no two elements have the same key. 2. The key in the left subtree are smaller than the key in the root 3. The key in the right subtree ...
- Saraswathi Velu College of Engineering
- Saraswathi Velu College of Engineering

... Collision occurs when a hash value of a record being inserted hashes to an address that already contains different record.(ie) when 2 key values hash to the same position. 7. What is collision Resolution? It is the process of finding another position for the collide record. 8. List the Collision Res ...
Data Structures
Data Structures

... of list. Much slower than ArrayList for access by position and iterating over. Uses a hash table. Requires that stored objects override hashCode() and equals(). Uses a doubly linked list as well as a hash table. This allows elements to be iterated over in insertion order rather than unpredictable or ...
Document
Document

... Insert the point into the correct leaf page, if it fits If a leaf overflows, it is split according to the ‘next’ dimension, using the median value as the discriminator. The split information is propagated to the parent page. If the parent overflows, it is split into two. A new split plane is chosen ...
Distributed Hash Tables
Distributed Hash Tables

... East Asia ...
Distributed Hash Tables: An Overview
Distributed Hash Tables: An Overview

YEAR / SEM : II/ III
YEAR / SEM : II/ III

... the keys in its left sub tree are smaller than the key value in X and the values of all the keys in its right sub tree are larger than the key value in X. 15. How deletion is performed in a binary search tree. Once the node to be deleted is found there are three possibilities 1. If the node is a lea ...
CSE 326 -- Don`t Sweat It
CSE 326 -- Don`t Sweat It

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lecture6

Data Structures
Data Structures

... contains rootItem //and has leftTree and rightTree, respectively, as its left and right subtrees destroyBinaryTree() // destroys a binary tree rootData() // returns the data portion of the root of a nonempty binary tree setRootData(newItem) // replaces the the data portion of the root of a //nonempt ...
< 1 ... 54 55 56 57 58 59 60 61 62 ... 76 >

Interval tree

In computer science, an interval tree is a tree data structure to hold intervals. Specifically, it allows one to efficiently find all intervals that overlap with any given interval or point. It is often used for windowing queries, for instance, to find all roads on a computerized map inside a rectangular viewport, or to find all visible elements inside a three-dimensional scene. A similar data structure is the segment tree.The trivial solution is to visit each interval and test whether it intersects the given point or interval, which requires O(n) time, where n is the number of intervals in the collection. Since a query may return all intervals, for example if the query is a large interval intersecting all intervals in the collection, this is asymptotically optimal; however, we can do better by considering output-sensitive algorithms, where the runtime is expressed in terms of m, the number of intervals produced by the query. Interval trees have a query time of O(log n + m) and an initial creation time of O(n log n), while limiting memory consumption to O(n). After creation, interval trees may be dynamic, allowing efficient insertion and deletion of an interval in O(log n). If the endpoints of intervals are within a small integer range (e.g., in the range [1,...,O(n)]), faster data structures exist with preprocessing time O(n) and query time O(1+m) for reporting m intervals containing a given query point.
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