Stack Vs. Queue: Key Differences, Uses & Examples in Data Structures

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Stacks and queues are two basic linear data structures of prime importance in computer science and programming alike. They are both meant for organizing and storing data elements in a certain order, but the use of these ordered elements makes them heaven apart.

In this article, we will explore the difference between a stack and a queue to understand how each structure functions and where they are best applied. We’ll begin by briefly introducing both data structures, followed by a comparison of their key differences, similarities, use cases, and practical examples. Let’s dive in!

Introduction to Stack Data Structure

A stack is an orderly arrangement of data in which the most recently added data is the first to be removed or accessed. In layman's terms, the last element to be added to the stack is the first to go out.  The stack operates in a way that new elements are pushed onto the top of the stack, and elements are popped off from the top.

Stacks are commonly used in a variety of applications in computer science, especially for managing function calls, processing expressions, and handling backtracking algorithms.

Features of Stack Data Structure

LIFO (Last In, First Out) Behavior: The stack follows the principle where the last element added is the first one to be removed, providing a way to reverse data order.

Push Operation: The push operation is used to add an element to the top of the stack. It increases the size of the stack by one.

Pop Operation: The pop operation removes the topmost element from the stack. It decreases the size of the stack by one.

Peek/Top Operation: The peek or top operation allows access to the element at the top of the stack without removing it, providing a view of the last element inserted.

IsEmpty Operation: This operation checks whether the stack is empty or not, ensuring that no pop or peek operation is performed when the stack has no elements.

Size Operation: This operation returns the current number of elements in the stack, which helps in tracking its size.

Efficient Access: Stack operations such as push, pop, and peek are typically implemented in constant time, O(1), making it an efficient data structure for many applications.

Memory Management: Stacks are often used to manage memory for function calls, particularly in recursive algorithms. Each function call is pushed onto the stack and popped when the function returns.

Simple Implementation: Stacks can be easily implemented using arrays or linked lists, providing flexibility in their use while maintaining a simple underlying structure.

Introduction to Queue Data Structure

A queue is a linear data structure that follows the First In First Out (FIFO) principle. In essence, the first element added to the queue is the first to be demolished from the queue. It resembles a real queue at the ticket counter: whoever arrives first is served first. Queues are paramount in situations where data is acted upon in the order of its arrival.

Features of Queue Data Structure

FIFO (First In, First Out) Principle: The first element added to the queue is the first one to be removed, ensuring that data is processed in the order it arrives.

Enqueue Operation: The enqueue operation adds an element to the rear of the queue, increasing the queue size.

Dequeue Operation: The dequeue operation removes the element from the front of the queue, decreasing the queue size.

Front Operation: This operation allows you to view the element at the front of the queue without removing it, providing access to the first element.

Rear Operation: The rear operation provides access to the element at the rear of the queue without removing it.

Is Empty Operation: This operation checks if the queue is empty, ensuring that dequeue and front operations are not performed on an empty queue.

Size Operation: The size operation returns the number of elements currently in the queue, offering insight into the queue’s current state.

Efficient Data Management: Queue operations like enqueue and dequeue are performed in constant time, O(1), making it a highly efficient structure for managing ordered data.

Simple to Implement: Queues can be easily implemented using arrays, linked lists, or circular buffers, offering flexibility in choosing the appropriate structure based on the use case.

Supports Multi-Tasking and Scheduling: Queues are frequently used in systems that require handling multiple tasks or processes, such as CPU scheduling, network data buffering, and task management.

Key Differences Between Stack and Queue

How Does a Stack Work?

LIFO Principle (Last In, First Out): The stack operates on the Last In, First Out (LIFO) principle. This means that the last element added to the stack is the first one to be removed.

Elements are Added to the Top: New elements are always added to the top of the stack using the push operation.

Elements are Removed from the Top: Elements are removed from the top of the stack using the pop operation, ensuring that the most recently added element is processed first.

Limited Access to Data: In a stack, only the top element is accessible at any given time. Other elements cannot be accessed directly until the top element is removed.

Fixed Size or Dynamic Size: A stack can either be implemented with a fixed size (using an array) or a dynamic size (using a linked list), depending on the needs of the application.

Stack Overflow & Underflow: Stack Overflow occurs when trying to add an element to a full stack. On the other hand, stack underflow occurs when trying to remove an element from an empty stack.

Used in Recursion and Backtracking: The stack is frequently used in recursion (for managing function calls) and backtracking algorithms (for exploring potential solutions).

Basic Operations in a Stack

Push Operation

• Adds an element to the top of the stack.
• Syntax: stack.push(element)

Pop Operation

• Removes the element from the top of the stack and returns it.
• Syntax: stack.pop()

Peek/Top Operation

• Views the element at the top of the stack without removing it.
• Syntax: stack.peek() or stack.top()

IsEmpty Operation:

• Checks whether the stack is empty.
• Syntax: stack.isEmpty()

Size Operation:

• • Returns the number of elements currently in the stack.
  • Syntax: stack.size()

Example of Stack

Let's say we have a stack of numbers, and we perform a series of operations:

Initial Stack: The stack is initially empty.

Push Operations: We push elements onto the stack:

stack.push(10)  → [10]

stack.push(20)  → [10, 20]

stack.push(30)  → [10, 20, 30]

Pop Operation: We pop an element from the stack:

stack.pop()  → Removes 30, stack is now [10, 20]

Peek Operation: We peek at the top element without removing it:

stack.peek()  → Returns 20 (top element), stack remains [10, 20]

Size Operation: We check the number of elements in the stack:

stack.size()  → Returns 2

IsEmpty Operation: We check if the stack is empty:

stack.isEmpty()  → Returns false (stack is not empty)

In this example, the stack begins as empty. We push elements, then pop one, peek at the top, and check the size and emptiness of the stack. The operations demonstrate how elements are added and removed in a stack, following the LIFO principle.

How Does a Queue Work?

FIFO Principle (First In, First Out)

A queue operates on the First In, First Out (FIFO) principle. This means the first element inserted is the first one to be removed.

Two Ends – Front and Rear

• Front is where elements are removed (dequeue).
• Rear is where elements are added (enqueue).

Elements Enter at the Rear

New elements are always inserted at the rear of the queue using the enqueue operation.

Elements Exit from the Front: Elements are removed from the front of the queue using the dequeue operation.

Fixed or Dynamic Size: Queues can be implemented using arrays (fixed size) or linked lists (dynamic size), depending on the requirements.

Efficient Processing Order: Queues ensure that tasks are processed in the order they arrive, making them ideal for scheduling and sequential task execution.

Overflow & Underflow: Queue Overflow occurs when adding to a full queue (in fixed-size implementations). Queue Underflow happens when trying to remove from an empty queue.

Widely Used in Real-World Systems: Queues are used in CPU scheduling, printing jobs, customer service systems, and more, any scenario where tasks need to be handled in arrival order.

Basic Operations on a Queue

Enqueue Operation:

• Adds an element to the rear of the queue.
• Syntax: queue.enqueue(element)

Dequeue Operation:

• Removes the element from the front of the queue and returns it.
• Syntax: queue.dequeue()

Front Operation:

• Returns the element at the front without removing it.
• Syntax: queue.front()

Rear Operation:

• Returns the element at the rear without removing it.
• Syntax: queue.rear()

IsEmpty Operation:

• Checks whether the queue is empty.
• Syntax: queue.isEmpty()

Size Operation:

• Returns the number of elements currently in the queue.
• Syntax: queue.size()

Example of a Queue

Let’s walk through a simple queue of numbers and operations:

Initial Queue: The queue is empty.

Enqueue Operations: We add elements to the queue:

• queue.enqueue(10)  → [10]
• queue.enqueue(20)  → [10, 20]
• queue.enqueue(30)  → [10, 20, 30]

Dequeue Operation: We remove an element from the front:

• queue.dequeue()  → Removes 10, queue becomes [20, 30]

Front & Rear Operations: Check elements at both ends:

• queue.front() → Returns 20 
• queue.rear()  → Returns 30

Size Operation: queue.size() → Returns 2

IsEmpty Operation: queue.isEmpty() → Returns false

This example shows how a queue processes data in the order it arrives, removing elements from the front and adding to the rear, perfectly following the FIFO model.

Implementation Difference Between Stack & Queue

The key difference between a stack and a queue lies in how elements are added and removed, and this directly impacts their implementation. 

Let’s explore the implementation differences between a stack and a queue in detail, along with examples for better understanding.

Data Access Pattern

Stack:

• Follows Last In, First Out (LIFO) order.
• Elements are added and removed from the same end (called the top).
• Only one end is used for both push and pop.

Queue:

• Follows First In, First Out (FIFO) order.
• Elements are added at the rear and removed from the front.
• Two ends are used: one for enqueue, one for dequeue.

Implementation Methods

Both stack and queue can be implemented using the following:

Stack Using Array: A stack uses a single index (top).

Queue Using Array: A queue uses two indices (front and rear) to track positions.

Stack Using Linked List: In a stack, elements are inserted and removed from the same end (top).

Queue Using Linked List: In a queue, elements are inserted at the rear and removed from the front, requiring tracking of two pointers.

Stack vs. Queue: Memory Efficiency, Simplicity & Use Cases

Applications of Stack and Queue Data Structures

Similarities Between Stack and Queue

Linear Data Structures: Both stack and queue are linear data structures, where elements are stored in a sequential manner and processed based on specific rules.

Dynamic or Static Implementation: Both can be implemented using arrays (static) or linked lists (dynamic), offering flexibility based on memory needs.

Homogeneous Data Handling: Both structures store homogeneous elements, meaning elements of the same data type are stored and processed.

Memory Usage: Both use contiguous or linked memory depending on whether they’re implemented using arrays or linked lists.

Basic Operation Set: Each supports a defined set of basic operations (e.g., push/pop for stack, enqueue/dequeue for queue) that manage data efficiently.

Efficient Time Complexity: Both offer O(1) time complexity for insertion and deletion operations (when implemented properly without shifting elements).

No Random Access: Neither allows random access to elements; access is restricted based on the order of insertion (LIFO for stack, FIFO for queue).

Used in Problem Solving: Both are extensively used in algorithm design, including recursion handling, scheduling, searching, and traversal problems.

Overflow and Underflow Conditions: Both can experience overflow and underflow scenarios in static implementations when trying to insert into a full structure or remove from an empty one.

Widely Supported in Programming Languages: Both are standard data structures, available in the standard libraries of most modern programming languages like C++, Java, Python, etc.

Conclusion

Both stack and queue are fundamental linear data structures that play crucial roles in various computational processes and real-world applications. A stack is a data structure that works on the Last In, First Out principle (LIFO); thus, it is best suited for purposes such as management of recursion, backtracking, and expression evaluation. On the other hand, a queue is a data structure that works on the First In, First Out method (FIFO); therefore, it is best for scheduling, buffering, and appending work according to its subjective arrival.

Though these structures differ in their working principles, they share some intrinsic similarities in structure and can be implemented through a combination of structural methods using either arrays or linked lists. Knowing such differences and similarities, as discussed in this article, would help with choosing the right data structure for any specific problem or system requirement. A thorough knowledge of these data structures will allow any developer to code more efficiently, systematically, and effectively across a spectrum of software development applications.

Frequently Asked Questions (FAQs)

Q1. What is the primary difference between Stack and Queue Data Structures with real-life examples?

The primary difference between a stack and a queue lies in how elements are inserted and removed. A stack follows the Last In, First Out (LIFO) principle, meaning the last element added is the first to be removed. In contrast, a queue follows the First In, First Out (FIFO) principle, where the first element added is the first to be removed.

Real-life example of a stack: A stack of plates in a cafeteria. The last plate placed on top is the first one to be picked up.
Real-life example of a queue: A queue at a movie theater. The person who arrived first is served first, and new arrivals go to the back of the line. 

Q2. What is the difference between stack and queue memory usage?

Stacks and queues use memory differently due to their access patterns. A stack typically uses contiguous memory locations and is often implemented with arrays or linked lists. In recursive programming, the call stack uses stack memory, which is a reserved section of RAM for function calls and local variables.

A queue, especially in array-based implementations, often requires more complex memory management. As elements are dequeued from the front, the memory space isn't reused unless a circular queue or dynamic shifting is implemented. This can lead to inefficient memory usage in a standard queue unless carefully managed. Linked list implementations for both structures are more flexible in memory usage but introduce additional overhead for pointers.

Q3. What are the advantages of a Stack over a Queue?

Stacks have several advantages in specific computational contexts:

Function Call Management: Stacks are ideal for tracking function calls and returns using the system call stack.

Backtracking: In scenarios like maze-solving or undo features in editors, stacks allow quick reversal of steps.

Expression Evaluation: Stacks simplify the process of converting and evaluating expressions (e.g., infix to postfix).

Simple Implementation: Stacks often require only a single pointer (top), making them simpler to implement than queues, which require both front and rear.

While queues are better for orderly processing, stacks are superior in problems requiring last-in processing or reversal.

Q4. Can a stack and a Queue be implemented using Linked Lists?

Yes, both stacks and queues can be implemented efficiently using linked lists. In a stack, elements are typically added and removed from the head of the linked list, making push and pop operations O(1).

In a queue, a linked list allows for O(1) enqueue and dequeue operations when both head (front) and tail (rear) pointers are maintained. This approach avoids the limitations of fixed-size arrays and the shifting problem in array-based queues, offering dynamic sizing and better memory utilization.

Q5. When should I use a Stack vs. a Queue in programming?

The choice between using a stack or a queue depends on the problem’s requirements:

Use a stack when:

• You need to reverse data or undo previous actions.
• The most recently added data should be processed first.
• Working with recursive functions or parsing expressions.

Use a queue when:

• Tasks should be processed in the order they arrive.
• You’re handling events, buffers, or job scheduling.
• Implementing algorithms like Breadth-First Search (BFS) that require orderly traversal.

Understanding the nature of the data and the required processing order is key to selecting the right structure.

This article was contributed by Johns Joseph, Unstop Intern and Campus Ambassador.

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