• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Trees
Trees

... • (c) F, A, D, and G are to the right of I (from (a) 2) • (d) C is the first left node of I (from (c) and 1) • (e) D is the first right node of I (from (c) and 1) • (f) possibly we have • B to the left of C, • E to the left of B, • H to the right of B … as this satisfies 1 and 2 • (g) F and A are le ...
Chapter12
Chapter12

... Successor and predecessor • Assuming that all keys are distinct, the successor of a node x is the node y such that y.key is the smallest key > x.key. (We can find x’s successor based entirely on the tree structure. No key comparisons are necessary.) If x has the largest key in the binary search tre ...
Binary Search Trees
Binary Search Trees

Problem Set 3 - Princeton CS
Problem Set 3 - Princeton CS

Trees Informal Definition: Tree Formal Definition: Tree
Trees Informal Definition: Tree Formal Definition: Tree

... build and use explicit data structures that are concrete realizations of trees describe the dynamic properties of algorithms ...
Trees Types and Operations
Trees Types and Operations

1 Persistent Data Structures
1 Persistent Data Structures

... • numerous special-purpose solutions • One solution: – vertical line through each vertex – divides into slabs – in slab, segments maintain one vertical ordering – find query point slab by binary search – build binary search tree for slab with “above-below” queries – n binary search trees, size ...
Data Structures for Midterm 2
Data Structures for Midterm 2

CS 315 Week 2 (Feb 5 and 7) summary and review questions
CS 315 Week 2 (Feb 5 and 7) summary and review questions

Key
Key

... __T __ Branch extends its superclass to a tree structure. _F___ A SoundNode object’s call to getNext() would return a SoundNode object. getNext() is inherited from the ...
Outline Notes
Outline Notes

... class, the left and right child pointers are such that the data value on the left of any Node is less than it and the data value on the right is greater. This standard remains for this modified Binary Search Tree. In addition, each Node can see (and thus, must maintain) the parent node. The complexi ...
Data Structures Name:___________________________
Data Structures Name:___________________________

Data structure
Data structure

Trees
Trees

of a tree
of a tree

B Tree Index Files by Huy Nguyen
B Tree Index Files by Huy Nguyen

Document
Document

CSE 114 – Computer Science I Lecture 1
CSE 114 – Computer Science I Lecture 1

... – A binary tree has a left subtree & right subtree • Depth of a node – starting at a node, the number of steps up to reach the root • Depth of a tree – the maximum depth of any of its leaves ...
CS 104 Introduction to Computer Science and Graphics Problems
CS 104 Introduction to Computer Science and Graphics Problems

Slides 3 - USC Upstate: Faculty
Slides 3 - USC Upstate: Faculty

Lecture 2 — February 7, 2007 1 Overview
Lecture 2 — February 7, 2007 1 Overview

Exam Review 2 - City University of New York
Exam Review 2 - City University of New York

binary search tree - Wellesley College
binary search tree - Wellesley College

Binary Trees - Wellesley College
Binary Trees - Wellesley College

... path from n to a leaf below it. E.g., node G has height 1, node C has height 2, and node F has height 4. The depth of a node n is the length of the path from n to the root. E.g., node F has depth 0, node C has depth 1, and node G has D depth 2. A binary tree is height-balanced iff at every node n, t ...
Concurrent R
Concurrent R

< 1 ... 71 72 73 74 75 >

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.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report