• 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
2-3 Trees
2-3 Trees

Efficient implementation of lazy suffix trees
Efficient implementation of lazy suffix trees

1 23 Data Structures on Event Graphs Bernard Chazelle & Wolfgang Mulzer Algorithmica
1 23 Data Structures on Event Graphs Bernard Chazelle & Wolfgang Mulzer Algorithmica

... classic dictionary problem where we need to maintain a subset of a given universe. We can also imagine more complicated scenarios such as U = Rd with T (X) being the Delaunay triangulation of X. An event graph G = (V , E) specifies restrictions on the queries and updates that are applied to T (X). F ...
read it here
read it here

2-3 trees 2-3
2-3 trees 2-3

Recent developments in linear quadtree
Recent developments in linear quadtree

The Randomized Complexity of Maintaining the Minimum
The Randomized Complexity of Maintaining the Minimum

DRAFT: Succinct and I/O Efficient Data Structures for Traversal in
DRAFT: Succinct and I/O Efficient Data Structures for Traversal in

Linked List - asyrani.com
Linked List - asyrani.com

... • Arrays can become full as it depends on our defined array • Time consuming • Existing elements need to be moved ...
The Tree Data Model
The Tree Data Model

... If the name of a node is not important, we can represent a node by its label. However, the label does not always provide a unique name for a node, since several nodes may have the same label. Thus, many times we shall draw a node with both its label and its name. The following paragraphs illustrate ...
Chapter 19 Java Data Structures
Chapter 19 Java Data Structures

AN OVERVIEW OF QUADTREES, OCTREES, AND RELATED
AN OVERVIEW OF QUADTREES, OCTREES, AND RELATED

On Cartesian Trees and Range Minimum Queries
On Cartesian Trees and Range Minimum Queries

Energy Efficient In-Network Data Indexing for Mobile Wireless
Energy Efficient In-Network Data Indexing for Mobile Wireless

lab#4 Linked Lists - Data Structures CS322
lab#4 Linked Lists - Data Structures CS322

Document
Document

... the beginning of the array (n shifts) Therefore on average we need to do (0+n)/2 shifts for inserting a random element in the array. Normally, when we talk about the complexity of operations (i.e the number of steps needed to perform that operation) we don’t care about the multiplied or added consta ...
Experiment 5 Singly linked list with operations Create, Insert, Delete
Experiment 5 Singly linked list with operations Create, Insert, Delete

9 Data Structures for Disjoint Sets (October 10 and 15)
9 Data Structures for Disjoint Sets (October 10 and 15)

List
List

The Random Access Zipper: Simple, Purely
The Random Access Zipper: Simple, Purely

... and focus to move the cursor to any other element. We provide more detailed examples of these actions in section 2. Our implementation of the RAZ requires under 200 lines of OCaml. This code includes ten main functions, each with at most a case select over the inputs, a recursive call, and one non-t ...
Chapter x - CHAPTER TITLE
Chapter x - CHAPTER TITLE

Max Chickering at Microsoft Research
Max Chickering at Microsoft Research

Pointers
Pointers

Chapter 19 Data Structures
Chapter 19 Data Structures

... • Linked list elements can only be accessed sequentially e.g., to find the 5th element, you must start from head and follow the links through four other nodes ...
Design Patterns for Self-Balancing Trees
Design Patterns for Self-Balancing Trees

< 1 ... 14 15 16 17 18 19 20 21 22 ... 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