What Is Tree in Data Structure Geeksforgeeks?


Angela Bailey

A tree is a widely used data structure in computer science and is an essential concept to understand for any aspiring programmer. In this article, we will delve into the world of trees, exploring what they are and how they are used in data structures.

What is a Tree?

A tree is a hierarchical data structure that consists of nodes connected by edges. It resembles a real-life tree with branches extending from a central trunk.

The topmost node in a tree is called the root, while the nodes at the bottom are called leaves. Nodes in between are referred to as internal nodes.

Basic Terminology

Before we dive deeper into trees, let’s familiarize ourselves with some basic terminology:

  • Node: Each element in a tree is called a node. A node can contain data and references to other nodes.
  • Edge: An edge represents the link or connection between two nodes.
  • Root: The topmost node in a tree is known as the root node. It serves as the starting point for traversing the tree.
  • Leaf: A leaf node is any node that does not have any children.

    In other words, it is a node that does not have any outgoing edges.

  • Parent: A parent node is the immediate predecessor of another node. For example, if Node B has an edge connecting it to Node A, then Node A is considered as the parent of Node B.
  • Child: A child node is directly connected to another node via an edge. If Node B has an edge connecting it to Node A, then Node B is considered as the child of Node A.

Types of Trees

Trees can be classified into various types based on their properties and organization. Here are some of the most common types:

  • Binary Tree: A binary tree is a tree in which each node can have at most two children, known as the left child and the right child.
  • Binary Search Tree (BST): A binary search tree is a binary tree in which the left child of a node contains a value less than the node’s value, and the right child contains a value greater than or equal to the node’s value. This property enables efficient searching, insertion, and deletion operations.
  • AVL Tree: An AVL tree is a self-balancing binary search tree in which the heights of the left and right subtrees differ by at most one.

    This balance ensures efficient operations even in dynamic scenarios.

  • B-tree: A B-tree is a self-balancing search tree that allows efficient storage and retrieval of large amounts of data. It is commonly used in databases and file systems.

Applications of Trees

Trees find applications in various domains due to their versatile nature. Here are some common applications:

  • Hierarchical Structures: Trees are suitable for representing hierarchical structures such as file systems, organization charts, XML/HTML documents, etc.
  • Sorting and Searching: Binary search trees facilitate efficient searching, sorting, and indexing operations on large datasets.
  • Decision Making: Decision trees are used in machine learning algorithms to make decisions based on given inputs.
  • Network Routing: Trees are used in network routing algorithms to find the most efficient path for data transmission.

Understanding trees and their applications is crucial for mastering various algorithms and data structures. By grasping the concepts of trees, you can develop more efficient and optimized solutions to a wide range of problems.

So, the next time you come across a tree in the context of data structures, remember its hierarchical nature and the various types and applications it encompasses.

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