• Study Resource
  • Explore Categories
    • 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
Lecture 2 — February 7, 2007 1 Overview
Lecture 2 — February 7, 2007 1 Overview

trees - Simpson College
trees - Simpson College

...  The method of choice in many applications ...
B+ Tree
B+ Tree

... Start at root, find leaf L where entry belongs. Remove the entry. › If L is at least half-full, done! › If L has only d-1 entries,  Try to re-distribute, borrowing from sibling (adjacent node with same parent as L).  If re-distribution fails, merge L and sibling. ...
Data Structures in Java
Data Structures in Java

... nodes such that the next node in the sequence is a child of the previous ...
1 Balanced Binary Search Trees
1 Balanced Binary Search Trees

... Exercise. Find the best c you can which satisfies the above inequalities. ...
red-black tree
red-black tree

Problem 7—Skewed Trees Trees are particularly annoying to test
Problem 7—Skewed Trees Trees are particularly annoying to test

Lecture 3: Red-black trees. Augmenting data structures
Lecture 3: Red-black trees. Augmenting data structures

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 ...
Binary Trees: Notes on binary trees
Binary Trees: Notes on binary trees

19-TreeIntroBST
19-TreeIntroBST

Concurrent R
Concurrent R

Data Structures and Search Algorithms
Data Structures and Search Algorithms

FinalExamReviewS07
FinalExamReviewS07

... • You should be able to show how these algorithms perform on a given red-black tree (except for delete), and tell their running time ...
Document
Document

... Stacks – Linear structures Linear structure – Last In First Out (LIFO) Relative order of elements is maintained Can be built on a list or array. All operations are constant-time E.g.: The “undo” stack in an editor The operands and operators in a scientific ...
Chapter 10
Chapter 10

...  There are 3 ways to traverse a tree, that is, to visit every node:  Preorder traversal: visit the current node, then traverse its left subtree, then its right subtree  Postorder traversal: traverse the left subtree, then the right subtree, then visit the current node  Inorder traversal: travers ...
Binary Search Trees
Binary Search Trees

of a tree
of a tree

7 Data Structures – Binary Search Trees
7 Data Structures – Binary Search Trees

Binary Trees - Wellesley College
Binary Trees - Wellesley College

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

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

... Disadvantages of BST  The shape of the tree depends on the order of insertions, and it can be degenerated.  When inserting or searching for an element, the key of each visited node has to be compared with the key of the element to be inserted/found. Keys may be long and the run time may increase ...
1 (i) - the David R. Cheriton School of Computer Science
1 (i) - the David R. Cheriton School of Computer Science

... In a cycle there is a B every t positions … But these positions can be in arbitrary order Which i’s have a B, and how do we store it? Keep a vector of all positions 0 indicates no B 1 indicates a B Rank gives the position of B[“i”] in actual B array So: π(i) and π -1(i) in O(1) time & (1+ε)n lg n bi ...
Trees
Trees

... For trees, several well-defined visiting orders exist:  Depth first traversals  preorder (NLR) ... visit root, then left subtree, then right subtree  inorder (LNR) ... visit left subtree, then root, then right subtree  postorder (LRN) ... visit left subtree, then right subtree, then root  Bread ...
Data structure
Data structure

...  In Binary trees  All nodes contain two links  None, one, or both of which may be NULL  The root node is the first node in a tree.  Each link in the root node refers to a child  A node with no children is called a leaf node ...
1 2 3 4 5 ... 62 >

Red–black tree

A red–black tree is a binary search tree with an extra bit of data per node, its color, which can be either red or black. The extra bit of storage ensures an approximately balanced tree by constraining how nodes are colored from any path from the root to the leaf. Thus, it is a data structure which is a type of self-balancing binary search tree.Balance is preserved by painting each node of the tree with one of two colors (typically called 'red' and 'black') in a way that satisfies certain properties, which collectively constrain how unbalanced the tree can become in the worst case. When the tree is modified, the new tree is subsequently rearranged and repainted to restore the coloring properties. The properties are designed in such a way that this rearranging and recoloring can be performed efficiently.The balancing of the tree is not perfect but it is good enough to allow it to guarantee searching in O(log n) time, where n is the total number of elements in the tree. The insertion and deletion operations, along with the tree rearrangement and recoloring, are also performed in O(log n) time.Tracking the color of each node requires only 1 bit of information per node because there are only two colors. The tree does not contain any other data specific to its being a red–black tree so its memory footprint is almost identical to a classic (uncolored) binary search tree. In many cases the additional bit of information can be stored at no additional memory cost.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report