What Is Linear Data Structure Explain With Example?


Scott Campbell

A linear data structure is a type of data structure where elements are stored in a sequential manner, such that each element has a successor and predecessor, except for the first and last elements. In other words, it is a collection of elements that are arranged in a linear order.


An example of a linear data structure is an array. An array is a fixed-size collection of elements of the same type, where each element can be accessed using its index. The index starts from 0 for the first element and increments by 1 for each subsequent element.

Let’s consider an example where we have an array named “numbers” that stores integers:

var numbers = [10, 20, 30, 40, 50];

In this example, the array “numbers” contains five elements: 10, 20, 30, 40, and 50. The first element (10) has an index of 0, the second element (20) has an index of 1, and so on.

Advantages of Linear Data Structures:

  • Easy access to elements: In linear data structures like arrays or linked lists, accessing any element requires only constant time complexity (O(1)). This makes it efficient to retrieve or modify specific elements.
  • Efficient memory utilization: Linear data structures allow efficient memory utilization as they store elements contiguously in memory (in the case of arrays). This allows for easy traversal and manipulation.

Different Types of Linear Data Structures:

There are several types of linear data structures commonly used in computer science:

1. Arrays:

Arrays are one-dimensional collections that store elements in contiguous memory locations. They provide constant-time access to individual elements but have a fixed size.

2. Linked Lists:

Linked lists consist of nodes, where each node stores the data and a reference to the next node in the list.

Linked lists can be singly linked (with a reference to the next node) or doubly linked (with references to both the next and previous nodes). They allow for dynamic memory allocation but have slower access times compared to arrays.

3. Stacks:

Stacks are linear data structures that follow the Last-In-First-Out (LIFO) principle.

Elements can only be inserted or removed from one end of the stack, known as the top. Common operations on stacks include push (insert an element) and pop (remove an element).

4. Queues:

Queues are linear data structures that follow the First-In-First-Out (FIFO) principle.

Elements can only be inserted at one end, called the rear, and removed from the other end, called the front. Common operations on queues include enqueue (insert an element) and dequeue (remove an element).


Linear data structures are essential in computer science as they provide efficient ways to store and manipulate data in a sequential manner. Understanding these structures is crucial for building efficient algorithms and solving complex problems.

By incorporating linear data structures like arrays, linked lists, stacks, and queues into your programs, you can optimize memory usage and improve performance.

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