What Is Tree in Data Structure and Its Properties?


Larry Thompson

A tree is a widely used data structure in computer science that represents a hierarchical structure. It is composed of nodes connected by edges, where each node can have zero or more children. In this article, we will explore the concept of trees in data structures and discuss their properties.

Tree Terminology

Before diving into the properties of trees, let’s familiarize ourselves with some common terminology related to trees:

  • Node: Each element in a tree is called a node. It contains some data and may have references to its child nodes.
  • Root: The topmost node in a tree is known as the root node.

    It serves as the starting point for accessing other nodes in the tree.

  • Parent: A node that has one or more child nodes is called a parent node.
  • Child: A node that has a parent node directly above it is referred to as its child node.
  • Sibling: Nodes that have the same parent are called siblings.
  • Leaf: A leaf node is a terminal node that does not have any children.
  • Edge: The connection between two nodes is called an edge. It represents the relationship between parent and child nodes.

Main Properties of Trees

Trees possess several key properties that make them useful for organizing and accessing data efficiently. Let’s explore these properties one by one:

Hierarchical Structure

A significant characteristic of trees is their hierarchical structure. This means that all nodes, except for the root, have exactly one parent node. It allows for the representation of relationships between different elements in a structured manner.

One Path Between Any Two Nodes

In a tree, there is always one unique path between any two nodes. This property ensures that each node can be accessed from the root node through a unique sequence of edges.

Root Node

The root node serves as the entry point to the tree. It is the only node without a parent and acts as the starting point for traversing the entire tree structure.

Leaf Nodes

Leaf nodes are nodes that do not have any children. They represent the endpoints of a tree structure and are often used to store data or perform specific operations.

Height of a Tree

The height of a tree is defined as the maximum number of edges from the root to any leaf node. It indicates the length of the longest path in the tree.

Types of Trees

Trees can be classified into various types based on their characteristics and arrangements. Some commonly used types include:

  • Binary Tree: A binary tree is a type of tree where each node has at most two children, known as left child and right child.
  • Binary Search Tree (BST): A binary search tree is a binary tree with an additional property that all elements in the left subtree are smaller than or equal to the root, and all elements in the right subtree are greater than or equal to the root. This property allows for efficient searching, insertion, and deletion operations.
  • Balanced Tree: A balanced tree is a type of tree where the difference between heights of left and right subtrees for every node is limited.

    It helps in maintaining optimal search and retrieval times.

  • AVL Tree: An AVL tree is a self-balancing binary search tree where the heights of left and right subtrees differ by at most one. It ensures that the tree remains balanced after insertion or deletion operations.

These are just a few examples, and there are many more types of trees that serve specific purposes based on different requirements.


Trees are fundamental data structures that provide an organized way of representing hierarchical relationships. They offer efficient methods for accessing, searching, and manipulating data. Understanding the properties and types of trees is essential for designing efficient algorithms and solving complex problems in computer science.

Now that you have a solid understanding of what trees are and their properties, you can explore more advanced topics such as tree traversal algorithms, balancing techniques, and applications of trees in various domains.

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