What Is Tree in Data Structure and Algorithm?


Heather Bennett

A tree is a widely used data structure in computer science and algorithms. It is a hierarchical structure that resembles a real-life tree with branches and leaves. In this article, we will explore what a tree is, its components, and how it is used in various algorithms.

Tree Structure

In a tree, each element is called a node. The topmost node of the tree is known as the root.

From the root, branches or edges extend to other nodes, which are called children. Nodes that have the same parent are known as siblings, and nodes that don’t have any children are referred to as leaves.

Types of Trees

Trees can be classified into several types based on their characteristics:

  • Binary Tree: A binary tree is a type of tree where each node can have at most two children, referred to as the left child and the right child.
  • Balanced Tree: A balanced tree is one where the height difference between the left and right subtrees of any node is not greater than one.
  • Binary Search Tree (BST): A binary search tree is a special type of binary tree where the values of all nodes in the left subtree are less than or equal to the node’s value, and values in the right subtree are greater.
  • Heap: A heap is a complete binary tree where every parent node has a value greater than or equal to its children (in case of max heap).
  • Trie (Prefix Tree): A trie or prefix tree is an ordered tree-based data structure used to store a dynamic set or associative array where the keys are usually strings.

Tree Traversal

Traversal is the process of visiting each node in a tree in a specific order. Two commonly used traversal techniques are:

  • Depth-First Traversal: In depth-first traversal, we explore as far as possible along each branch before backtracking. It can be done in three ways:
    • Pre-order: Visit the root, traverse left subtree, then traverse right subtree.
    • In-order: Traverse left subtree, visit the root, then traverse right subtree.
    • Post-order: Traverse left subtree, traverse right subtree, then visit the root.
  • Breadth-First Traversal: In breadth-first traversal (also known as level order traversal), we visit nodes at each level before moving to the next level.

Applications of Trees

Trees have various applications in computer science and algorithms. Some common use cases include:

  • Hierarchical Structures: Trees are used to represent hierarchical relationships between elements like file systems or organization structures.
  • Searching and Sorting: Binary search trees provide efficient searching and sorting operations with a time complexity of O(log n) on average.
  • Graph Algorithms: Trees serve as a foundation for graph algorithms like spanning trees and shortest path algorithms.
  • Decision Trees: Decision trees are used in machine learning for decision-making processes based on given conditions or features.
  • Compression Algorithms: Huffman coding, a compression algorithm, uses a binary tree to assign shorter codes to frequently occurring characters.

Understanding trees and their applications is essential for solving many complex problems efficiently. Whether you’re working on data structures or algorithms, having a good grasp of trees will undoubtedly enhance your problem-solving skills.

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