# What Is Non Terminal Node in Data Structure?

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Larry Thompson

In the field of data structures, a non-terminal node is a fundamental concept that plays a crucial role in various data structure operations. Understanding what a non-terminal node is and how it relates to other nodes in a data structure is essential for efficient data manipulation and retrieval.

In this article, we will delve into the details of non-terminal nodes and explore their significance in different data structures.

## Definition of Non-Terminal Node

A non-terminal node, also known as an internal node or an intermediate node, is a node within a data structure that has child nodes connected to it. In contrast to a terminal node or leaf node, which does not have any children, a non-terminal node acts as an intermediary between the root node and the leaf nodes in a hierarchical structure.

Non-terminal nodes are present in various types of data structures such as trees, graphs, and linked lists. These nodes serve as branching points or decision points where different paths or branches originate.

They facilitate efficient traversal and manipulation of data by organizing and connecting multiple child nodes.

## Characteristics of Non-Terminal Nodes

Non-terminal nodes possess certain characteristics that distinguish them from other types of nodes within a data structure:

• Child Nodes: Non-terminal nodes have one or more child nodes connected to them.
• Parent Node: Each non-terminal node (except the root) has exactly one parent node.
• Branching Points: Non-terminal nodes serve as branching points where multiple paths originate.
• Data Storage: Non-terminal nodes may store information or references to relevant data.
• Connectivity: They establish connections between different levels or layers of a data structure.

These characteristics enable non-terminal nodes to provide structure and organization to data, allowing for efficient traversal, searching, and manipulation operations.

## Examples of Non-Terminal Nodes in Data Structures

To better understand the concept of non-terminal nodes, let’s explore a few examples in common data structures:

### Trees:

In a binary tree, each non-terminal node has two child nodes – a left child and a right child. These nodes allow for the hierarchical representation of data where each parent node divides the tree into two sub-trees.

Non-terminal nodes in trees are commonly used in algorithms like binary search trees and heap structures.

### Graphs:

In a graph data structure, non-terminal nodes represent vertices or nodes that are connected by edges. These nodes play a vital role in establishing relationships between different elements in the graph.

They allow for efficient traversal, pathfinding algorithms like Dijkstra’s algorithm or breadth-first search (BFS), and various graph-based operations.

In linked lists, non-terminal nodes act as intermediate nodes that connect individual elements together. Each non-terminal node holds a reference to the next node in the list, forming a chain-like structure.

They facilitate efficient insertion and deletion operations by modifying these references.

## Conclusion

Non-terminal nodes are essential components of various data structures like trees, graphs, and linked lists. These nodes provide structure and organization to data by connecting multiple child nodes together.

Understanding the characteristics and significance of non-terminal nodes is crucial for effectively manipulating and retrieving data from these structures. Whether you’re working with trees, graphs, or linked lists, recognizing non-terminal nodes’ role will help you design efficient algorithms and optimize your data operations.