Lect 21 Zaheer Abbas
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The document defines and describes various types of trees, including binary trees. It explains that a tree is a non-linear data structure used to represent hierarchical relationships, with each node having up to two children. The document also defines key tree terms like root, parent and child nodes, leaf nodes, subtrees, and internal nodes. Specific tree types covered include binary trees, strictly binary trees, complete binary trees, extended binary trees, and binary search trees.
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The document defines and describes various types of tree data structures, including their components and properties. It explains that a tree consists of nodes connected by edges, with one root node at the top. The document also defines different types of nodes such as leaf nodes, internal nodes, and binary, complete, and binary search trees.
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9. Complete and Full Binary Tree
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Trees are hierarchical data structures that can represent relationships between data items. A tree consists of nodes connected by edges, with one root node at the top. Examples of trees include biological classification trees, file system directories, and HTML page elements.
Key terminology includes nodes, edges, the root node, leaf nodes, paths between nodes, parent and child relationships, subtrees, levels, heights, and depths. Binary trees have at most two child nodes per parent, and can be traversed in preorder, inorder, or postorder to visit the nodes.
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1. The document discusses trees as a non-linear data structure that can represent hierarchical relationships. It specifically focuses on binary trees, their basic structure, properties, representations, and converting general trees to binary trees.
2. Binary trees have properties like a root node, leaf nodes, parent and child nodes, as well as left and right subtrees. They can be represented sequentially using arrays or linked lists.
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7. m-ary Tree
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The document discusses different types of tree data structures, including general trees, binary trees, binary search trees, and their traversal methods. General trees allow nodes to have any number of children, while binary trees restrict nodes to having 0, 1, or 2 children. Binary search trees organize nodes so that all left descendants are less than the parent and all right descendants are greater. Common traversal orders for trees include preorder, inorder, and postorder, which differ in whether they process the root node before or after visiting child nodes.
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1. Trees are non-linear data structures that represent hierarchical relationships. They consist of nodes connected by edges, with one node designated as the root.
2. Trees can be represented using arrays or linked lists. Array representation requires knowing the height of the tree in advance, while linked lists do not waste memory but have slower access times.
3. Common tree terminology includes root, leaf nodes, internal nodes, siblings, ancestors, descendants, depth, height, and subtrees. Binary trees restrict nodes to at most two children each.
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- A tree is a connected graph without simple circuits. Properties include a unique path between vertices and no loops or multiple edges.
- Trees can be used to represent hierarchies and organize data. Examples include organizational charts and file systems.
- Binary search trees allow efficient searching through ordered data by storing keys so that all values in the left subtree are less than the root and all values in the right subtree are greater.
- Traversal algorithms like preorder, inorder and postorder visit the vertices of a rooted tree in a systematic way and have applications in parsing expressions and serializing data.
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1. The document discusses trees as a non-linear data structure that can represent hierarchical relationships. It specifically focuses on binary trees, their basic structure, properties, representations, and converting general trees to binary trees.
2. Binary trees have properties like a root node, leaf nodes, parent and child nodes, as well as left and right subtrees. They can be represented sequentially using arrays or linked lists.
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The document provides an overview of tree data structures, including binary trees and binary search trees. It defines key tree terms like root, leaf nodes, height, depth, etc. It describes different types of binary trees like complete, strictly binary, almost complete binary trees. It explains tree traversal algorithms like preorder, inorder and postorder. Binary search trees are described along with search, insertion and deletion operations. Linked and array representations of binary trees are also covered.
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The document discusses different types of tree data structures, including general trees, binary trees, binary search trees, and their traversal methods. General trees allow nodes to have any number of children, while binary trees restrict nodes to having 0, 1, or 2 children. Binary search trees organize nodes so that all left descendants are less than the parent and all right descendants are greater. Common traversal orders for trees include preorder, inorder, and postorder, which differ in whether they process the root node before or after visiting child nodes.
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This document discusses binary trees and their representations and uses. It defines key terms related to binary trees like nodes, leaves, siblings, and levels. It describes different types of binary trees like complete and extended binary trees. It explains how to represent binary trees in memory using linked and sequential representations. It provides examples of how binary trees can be used to represent expressions and model tournaments. It also discusses algorithms for traversing binary trees in preorder, inorder and postorder sequences.
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1. Trees are non-linear data structures that represent hierarchical relationships. They consist of nodes connected by edges, with one node designated as the root.
2. Trees can be represented using arrays or linked lists. Array representation requires knowing the height of the tree in advance, while linked lists do not waste memory but have slower access times.
3. Common tree terminology includes root, leaf nodes, internal nodes, siblings, ancestors, descendants, depth, height, and subtrees. Binary trees restrict nodes to at most two children each.
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- A tree is a connected graph without simple circuits. Properties include a unique path between vertices and no loops or multiple edges.
- Trees can be used to represent hierarchies and organize data. Examples include organizational charts and file systems.
- Binary search trees allow efficient searching through ordered data by storing keys so that all values in the left subtree are less than the root and all values in the right subtree are greater.
- Traversal algorithms like preorder, inorder and postorder visit the vertices of a rooted tree in a systematic way and have applications in parsing expressions and serializing data.
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Lect 22 Zaheer Abbas
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Lect 10 Zaheer Abbas
A linked list is a linear data structure where each element is linked to the next element via a pointer. Each element, called a node, contains data and a pointer to the next node. The first node is referenced by a pointer called the head. Linked lists allow for efficient insertion and removal of nodes throughout the list since nodes are not confined to adjacent memory locations. Linked lists can grow and shrink dynamically as nodes are added or removed.
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3. C# supports one-dimensional and multi-dimensional arrays. Elements in arrays are accessed using an index. Arrays are zero-indexed and bounds checked to prevent errors. The Length property provides the size of the array.
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AD3251-Data Structures Design-Notes-Tree.pdfRamco Institute of Technology, Rajapalayam, Tamilnadu, India
This document provides information about tree data structures and binary trees. It defines key tree terminology like nodes, leaves, ancestors, descendants. It also defines binary tree terms like complete binary tree, strictly binary tree, and expression trees. The document discusses tree traversals like inorder, preorder and postorder traversal. It provides examples of tree representations and operations like insertion, deletion and searching in binary search trees. It also covers heaps and their applications. Sample Python code is given to implement a binary search tree with functions for insertion, searching and deletion of nodes.Tree Introduction.pptx
Tree is a hierarchical data structure that stores information in a parent-child relationship. There are different types of trees including binary trees, binary search trees, and expression trees. Binary trees restrict each node to having zero, one, or two children while binary search trees further require that all left descendants of a node are less than the node and all right descendants are greater than or equal. Expression trees represent mathematical expressions with operators as internal nodes and operands as leaves.
Unit 3.ppt
This document discusses trees and binary trees. It defines key terminology like root, leaf nodes, internal nodes, and provides examples of different types of binary trees including full, complete, balanced, and binary search trees. It also covers different representations of binary trees using arrays and linked lists as well as common traversal techniques for binary trees like preorder, inorder and postorder traversal.
Tree and Binary Search tree
Tree and Binary search tree in data structure.
The complete explanation of working of trees and Binary Search Tree is given. It is discussed such a way that everyone can easily understand it. Trees have great role in the data structures.
trees in data structure
Tree and graph data structures are used to represent hierarchical data. A tree has nodes connected by edges in a parent-child relationship where each node can have zero or more children but only one parent, forming a rooted tree. Common tree types include binary trees where each node has at most two children, binary search trees where the left child is less than the parent which is less than the right child, and B-trees where nodes can have multiple children. Trees are traversed using in-order, pre-order and post-order algorithms.
Trees - Data structures in C/Java
This document discusses binary trees as a data structure for storing hierarchical data. It defines key tree terminology like root, parent, child, and leaf nodes. It provides examples of how binary trees can be used to represent expressions and for file compression. It also introduces a BinaryTreeNode inner class to represent individual nodes, with constructors to initialize the data, left, and right references. Code is provided to build sample trees from these nodes and an example recursive size method is given.
discrete mathematics binary%20trees.pptx
The document defines and explains key concepts related to binary trees including their terminology, properties, and different types. It discusses binary tree concepts such as parent, child, root, leaf nodes, subtrees, and full and complete binary trees. The document also covers spanning trees, minimal spanning trees, Prim's and Kruskal's algorithms for finding minimum spanning trees, and binary search trees.
Chapter 8: tree data structure
The document discusses trees and binary trees as data structures. It defines what a tree is, including parts like the root, parent, child, leaf nodes. It then defines binary trees as trees where each node has no more than two children. Binary search trees are introduced as binary trees where all left descendants of a node are less than or equal to the node and all right descendants are greater. The document concludes by discussing how to build a binary search tree class with Node objects.
Unit 4.1 (tree)
The document discusses topics related to trees and graphs. It covers definitions and concepts of trees, binary trees and their representations. It discusses operations on binary trees like tree traversals. Binary search trees and heap trees are also covered. The document also provides an introduction to graphs and discusses graph representations and traversals. It concludes with the topic of minimal spanning trees.
Unit iii(dsc++)
The document discusses trees and binary trees. It defines trees and binary trees, describes their terminology like root, leaf nodes, levels etc. It explains different representations of binary trees using arrays and linked lists. It also covers operations on binary search trees like insertion, deletion and searching. Tree traversals namely preorder, inorder and postorder are also explained.
DSA IV Unit.pptx
This document provides information about the course "Data Structures and Algorithms" taught at Matrusri Engineering College. It includes the course objectives, outcomes, units and topics covered. The topics covered include algorithms complexity, linear data structures like stacks and queues, non-linear structures like trees and graphs. It also discusses various searching and sorting techniques. Specifically, it provides detailed information about tree data structures - their properties, types, operations, representations and traversal algorithms.
Tree (Data Structure & Discrete Mathematics)
This slide was made for my University presentation .
In this slide is full of the basic of Tree.I hope, you will get most basic information from this slide.
Trees
An introduction to tree data structures, binary trees and related algorithms
Computer science principles
Unit 3,4.docx
This document discusses various tree data structures and algorithms. It begins by defining a tree as a hierarchical data structure consisting of nodes connected by edges. It then discusses different tree terminology like root, child, parent, leaves, siblings, etc. It describes different types of trees like binary trees and general trees. It covers implementations of trees using arrays and linked lists. It discusses various tree traversal algorithms like inorder, preorder and postorder traversals. It describes applications of trees like representing directories in a file system and calculating the size of directories. It covers binary search trees and algorithms for operations on them like search, insert, find minimum and find maximum.
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