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# Linear Data Structure

Last Updated on May 5, 2023 by Prepbytes

Data structures play a crucial role in solving complex problems. They are used to organize and store data in a way that allows efficient access, modification, and retrieval of the data. Having an understanding of the different types of data structures helps developers choose the most appropriate data structure in a particular situation. Data structures are classified into two types: linear and non-linear data structures. This article discusses linear data structures, characteristics of linear data structures, and types of linear data structures.

## What is Linear Data Structure?

A linear data structure is a type of data structure in which data elements are arranged in sequential order. Each element has a predecessor and successor, except for the first and last elements. Linear data structures are used when data elements need to be processed in a specific order, or when they can be represented as a linear sequence. As the elements are stored linearly, the data traversal is accomplished in a single run.

## Characteristics of Linear Data Structures

The characteristics of linear data structures are as follows:

1. Sequential order: In a linear data structure, the elements are arranged in sequential order, and each element has a predecessor and successor, except for the first and last elements.
2. Traversed in a single run: Linear data structures can be traversed in a single run, which means that each element can be accessed by following a specific order.
3. Contiguous memory allocation: The elements in a linear data structure are stored in a contiguous block of memory, which allows for efficient memory management.
4. Simple implementation: Linear data structures have a simple implementation and are easy to understand.
5. Efficient data retrieval: Linear data structures provide efficient data retrieval, as they allow for easy access to the required data elements.
6. Linear complexity: Linear data structures have a linear time complexity, which means that the time required to perform operations on these structures increases linearly with the size of the structure.

## Types of Linear Data Structures

Linear data structure types include arrays, linked lists, stacks, and queues. Let’s look at each one in a bit more detail.

### 1. Arrays

Arrays are a collection of elements of the same data type, which are stored in a contiguous block of memory. The elements in an array can be accessed using an index, which represents the position of the element in the array. Arrays have a fixed size, which means that the number of elements that can be stored is limited by the size of the array.

Properties:

1. Elements in an array are stored in a contiguous manner.
2. The elements in the array can be accessed at a constant time using the index.
3. In the worst scenario, the time complexity of searching an element within an array will be proportional to the size of the array.
4. Linear time complexity for element insertion and deletion i.e (O(n)).

Linked lists are a collection of nodes, each containing a data element and a pointer to the next node. The first node in the list is called the head, and the last node is called the tail. Linked lists can be singly linked, with each node pointing to the next node, or doubly linked, with each node pointing to both the next and previous nodes. Linked lists can grow and shrink dynamically, which means that they don’t have a fixed size.

Properties:

1. Linked lists don’t have a fixed size, they can grow and shrink dynamically.
2. The time complexity of accessing an element in a linked list is O(n).
3. The time complexity of searching for an element in a linked list is O(n).
4. The time complexity of inserting a node at the beginning of a linked list takes constant time. However, inserting a node at any other position in the list takes linear time because we may need to traverse the list to find the insertion point.
5. The time complexity of deleting an element in a linked list is O(n).

### 3. Stacks

Stacks are a collection of elements that follow the Last In First Out (LIFO) principle. The elements in a stack can only be added or removed from the top of the stack. The top of the stack is the last element that was added to the stack.

Properties:

1. Elements are stored in a linear sequence.
2. Dynamic size.
3. Constant time complexity for element insertion and deletion at the top of the stack (O(1)).
4. Linear time complexity for element access (O(n)).

### 4. Queues

Queues are a collection of elements that follow the First In First Out (FIFO) principle. The elements in a queue can only be added to the back of the queue and removed from the front of the queue. The front of the queue is the first element that was added to the queue.

Properties:

1. Elements are stored in a linear sequence.
2. Dynamic size.
3. Constant time complexity for element insertion at the back of the queue (O(1)).
4. Constant time complexity for element deletion at the front of the queue (O(1)).
5. Linear time complexity for element access (O(n)).

Conclusion
In conclusion, linear data structures are used extensively in various applications to organize and manipulate data efficiently. Arrays, linked lists, stacks, and queues are some of the commonly used linear data structures. Each of these data structures has unique properties and is suitable for specific use cases. With a thorough understanding of linear data structures, programmers can write efficient and effective code that meets the needs of modern computing.

## FAQs on Linear Data Structures

Here are some frequently asked questions on linear data structures.

Q1: What is the difference between an array and a linked list?
Ans: In an array, elements are stored in contiguous memory locations, whereas in a linked list, elements are stored in nodes that are not necessarily contiguous.

Q2: What is the time complexity of searching an element in a linear data structure?
Ans: The time complexity of searching an element in a linear data structure is O(n), where n is the size of the data structure.

Q3: What are the basic operations performed on a stack?
Ans: The basic operations performed on a stack are push, pop, and peek.

Q4: What is the time complexity of inserting an element in the middle of a linked list?
Ans: The time complexity of inserting an element in the middle of a linked list is O(n), where n is the size of the linked list.

Q5: What are the basic operations performed on a queue?
Ans: The basic operations performed on a queue are enqueue, dequeue, and peek.

Q6: What is the difference between a stack and a queue?
Ans: The main difference between a stack and a queue is the order in which elements are inserted and removed. In a stack, the last element inserted is the first one to be removed, while in a queue, the first element inserted is the first one to be removed.