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Data Structure - Hi
Data Structure - Hi

CSC401: Analysis of Algorithms
CSC401: Analysis of Algorithms

Mid-term exam
Mid-term exam

Complete Binary Trees
Complete Binary Trees

... will eventually reach the root.  Every node except the root has one parent. The root has no parent.  Complete binary trees require the nodes to fill in each level from left-to-right before starting the next level. ...
Complete Binary Trees
Complete Binary Trees

... Binary trees contain nodes.  Each node may have a left child and a right child.  If you start from any node and move upward, you will eventually reach the root.  Every node except the root has one parent. The root has no parent.  Complete binary trees require the nodes to fill in each level from ...
Session 1
Session 1

Succinct tree representations
Succinct tree representations

Trees
Trees

Persistent Data Structures 2.1 Introduction and motivation
Persistent Data Structures 2.1 Introduction and motivation

Trees - NEW
Trees - NEW

Notes
Notes

Chapter08
Chapter08

Trees - GearBox
Trees - GearBox

... ► Go to parent or children from a given node ► Add a root to an empty tree ► Add a child to a node ► Remove a node (can impose that the node be a leaf, for simplicity) ► Get the element associated to a node ► Replace the element associated to a node ...
Binary Tree
Binary Tree

... An array of data We don't care what's in this part of the array. ...
Slides for Exam 3 review
Slides for Exam 3 review

... – Disjoint sets and up-tree representation • representative of each set • direction of pointers ...
Slides - Department of Computer and Information Science and
Slides - Department of Computer and Information Science and

497-294 - Wseas.us
497-294 - Wseas.us

Applications of Trees
Applications of Trees

1a) Describe the characrteristics of a complete binary tree
1a) Describe the characrteristics of a complete binary tree

... Q. Let A be a collection of Objects. Describe an efficient method for converting A to a set. That is remove all duplicates from the collection. A. Simply define an additional storage location such as an array and copy all the objects to it checking to see that they do not already exist before copyin ...
cs2110-15-trees
cs2110-15-trees

Applications of Trees
Applications of Trees

document
document

...  This pathlength is determined by counting the number of links that must be followed to get from the root to the node  The root is considered to be level 0, the children of the root are at level 1, the grandchildren of the root are at level 2, and so on ...
Key
Key

Midterm (with solution)
Midterm (with solution)

... terms of H, what is the complexity in time (big-Oh notation) of the following operations. (a) Printing BST using the in order traversal. (b) Printing BST using the post order traversal. (c) Printing BST using the pre order traversal. 3. Redo the previous question if we assume that BST is a degenerat ...
Lists and Trees (continued)
Lists and Trees (continued)

... has more than one potential successor • Defines a partial order CS-2301 D-term 2009 ...
< 1 ... 52 53 54 55 56 57 58 59 60 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.
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