Top 12 Stack Examples in Real Life: Practical Applications And Use Cases

In 2025, India surpassed 900 million internet users, generating vast data requiring efficient structures like stacks for processing and storage. This surge underscores the need to understand fundamental data structures like stacks. 

A stack operates on the Last In, First Out (LIFO) principle, where the last item added is the first removed. This concept is vital in programming, system processes, and problem-solving. This article explores the top 12 real-life stack examples, demonstrating LIFO's role in daily activities.

Best 12 Stack Examples In Real Life: How LIFO Works In Daily Activities?

Stacks, fundamental in both computing and daily life, operate on the Last In, First Out (LIFO) principle. This means the last item added is the first to be removed.

 In data structures, a stack is represented as a collection where elements are added and removed from the top. The 'top' pointer indicates the current end of the stack. 

Key operations include:

• Push: Adds an element to the top.
• Pop: Removes the top element.
• Peek: Retrieves the top element without removing it.

Stacks can be implemented using arrays or linked lists. An array-based stack has a fixed size, leading to potential overflow if exceeded. Conversely, a linked list-based stack grows dynamically, reducing overflow risk.

Understanding these concepts is essential for recognizing how LIFO structures function in everyday scenarios.

1. Back And Forward Button In Web Browser

In web browsers, the back and forward buttons exemplify the Last In, First Out (LIFO) principle of stack data structures. Browsers maintain two stacks to manage your navigation history:

• Backward Stack: Stores URLs of pages you've visited.
• Forward Stack: Holds URLs for forward navigation.

When you visit a new page, it's pushed onto the backward stack, and the forward stack is cleared. Clicking the back button pops the current page from the backward stack, pushing it onto the forward stack, allowing you to revisit previous pages. This mechanism ensures efficient navigation through your browsing history.

2. UNDO/REDO In Text Editors And Image Editing Software

In text editors and image editing software, the UNDO and REDO functionalities are implemented using stack data structures, adhering to the Last In, First Out (LIFO) principle. 

Each user action—be it typing, drawing, or deleting—is encapsulated as a command and stored on an undo stack. This design allows for efficient reversal and reapplication of actions, ensuring a seamless user experience.

• UNDO Operation: When you perform an action, such as typing a word or applying a filter, it's pushed onto the undo stack. Activating the UNDO command pops the most recent action from this stack, reverting the document or image to its prior state. This action is then pushed onto a separate redo stack.
• REDO Operation: If you've undone an action and decide to reapply it, the REDO command pops the action from the redo stack and reapplies it. This action is subsequently pushed back onto the undo stack.

This stack-based approach ensures that actions can be reversed or reapplied in the exact order they were performed, ensuring smooth and intuitive user interactions.

Also Read: How to Implement Stacks in Data Structure? Stack Operations Explained

3. Memory Management In Computer Programming

In computer programming, memory management is crucial for efficient and error-free execution. A fundamental aspect of this is the call stack, which manages function calls and their execution contexts using the Last In, First Out (LIFO) principle.

• Function Call Process: When a function is invoked, an activation record or stack frame is created, containing the function's parameters, local variables, and the return address. This frame is pushed onto the top of the call stack.
• Execution Flow: The program executes the current function at the top of the stack. If this function calls another function, a new stack frame is pushed onto the stack. This process continues, creating a nested structure of function calls.
• Function Return: Once a function completes its execution, its stack frame is popped from the stack, and control returns to the function below it. This ensures that each function resumes precisely where it left off before making a new function call.

This LIFO structure is essential for handling nested and recursive function calls, maintaining the correct sequence of execution, and ensuring that each function's local variables and parameters are appropriately managed. 

Mastering this concept helps developers optimize performance and avoid stack overflow errors.

Also Read:  Difference Between Function and Method in Python

4. Delimiter Checking

Delimiter checking is essential in programming to ensure that symbols like parentheses, brackets, and braces are correctly balanced in expressions. This process utilizes a stack data structure to verify the proper pairing and nesting of these delimiters.

For example, consider the expression {[()]}. Using a stack, you can validate its correctness by:

• Pushing each opening delimiter ({, [, () onto the stack.
• Popping the stack when encountering a closing delimiter (), ], }) and checking if it matches the corresponding opening delimiter.

This method ensures that every opening symbol has a matching closing symbol in the correct order.

If the expression is incorrect, one of the following issues may occur:

• A closing delimiter appears without a matching opening delimiter.
• The stack is not empty at the end, indicating unmatched opening delimiters.
• A mismatched delimiter is found during popping.

Implementing delimiter checking with a stack involves:

• Iterating through each character in the expression.
• Pushing opening delimiters onto the stack.
• Popping the stack for closing delimiters and verifying matches.
• Ensuring the stack is empty at the end, indicating all delimiters are balanced.

This approach is widely used in compilers and interpreters to validate code syntax.

5. Implementing Recursion In Programming

In programming, recursion allows a function to call itself, enabling solutions to complex problems by breaking them down into simpler subproblems. This process relies on the call stack to manage active function calls. 

Each time a recursive function is invoked, an activation record (or stack frame) is pushed onto the call stack, storing the function's parameters, local variables, and return address. 

When the function reaches its base case—a condition that stops further recursive calls—the stack begins to unwind, popping each activation record and returning control to the previous function call. This LIFO behavior ensures that each function resumes precisely where it left off, maintaining the correct state throughout the execution.

Understanding this mechanism is crucial for implementing efficient recursive algorithms.

• Function Invocation: Each recursive call adds a new frame to the call stack, preserving the current state.
• Base Case: Prevents infinite recursion, avoiding excessive function calls that exceed stack memory, leading to a stack overflow error.
• Stack Unwinding: Upon reaching the base case, the call stack unwinds, returning results through the chain of function calls.

This stack-based management is fundamental to recursion's functionality in programming.

Also Read: Recursive Feature Elimination: What It Is and Why It Matters?

6. Expression Conversion And Evaluation

In computing, stacks are instrumental in converting and evaluating arithmetic expressions, particularly when transforming infix expressions (e.g., A + B) to postfix (AB+) or prefix (+AB) forms. This conversion facilitates easier and more efficient computation.

To understand the role of stacks in expression conversion and evaluation, consider the following points:

• Infix to Postfix Conversion: Stacks help manage operators and parentheses during the conversion process, ensuring correct operator precedence and association.
• Expression Evaluation: Postfix expressions can be evaluated efficiently using stacks by processing operands and operators in a specific order.

This stack-based approach is widely used in compilers and calculators to parse and evaluate mathematical expressions efficiently.

Also Read: Type Conversion & Type Casting in Python Explained with Examples

7. Matching HTML Tags In Web Development

In web development, ensuring that HTML tags are properly nested is crucial for correct webpage rendering. Browsers use stacks to ensure that each opening tag has a matching closing tag.

When an opening tag, such as <div>, is encountered, it's pushed onto the stack. Upon encountering a closing tag, like </div>, the browser pops the top tag from the stack and checks for a match. If the tags align correctly, the HTML structure is considered valid; otherwise, errors are identified.

For example, in the snippet <div><p></p></div>, the sequence of operations would be:

• Push <div> onto the stack.
• Push <p> onto the stack.
• Encounter </p>, pop <p> from the stack.
• Encounter </div>, pop <div> from the stack.

This process ensures that each opening tag has a corresponding closing tag in the correct order, maintaining the integrity of the HTML document.

Understanding this stack-based validation is essential for web developers to create well-structured and error-free HTML documents.

Also Read: Structure of HTML: The Essential Guide to Building Web Pages in 2025

8. Browser History

In web browsers, the history mechanism exemplifies the Last In, First Out (LIFO) principle inherent in stack data structures. When you navigate to a new webpage, the current URL is pushed onto the history stack. 

Clicking the back button pops the most recent URL from this stack, returning you to the previous page. This process ensures an intuitive navigation experience by retracing your steps in reverse order.

Key Points:

• History Stack: Stores URLs of previously visited pages, facilitating backward navigation.
• Push Operation: Adds the current URL to the history stack when a new page is visited.
• Pop Operation: Removes the top URL from the stack upon clicking back, displaying the preceding page.

This stack-based system is fundamental to web browsers, ensuring efficient and user-friendly navigation through your browsing history.

9. Syntax Parsing

In syntax parsing, stacks play a crucial role in ensuring that programming code adheres to defined grammar rules. Compilers utilize stacks to validate the proper nesting and structure of code elements, such as matching parentheses, braces, and control structures. This process is essential for translating high-level code into machine-readable instructions.

For instance, consider the validation of nested if-else statements:

• Proper Nesting: Ensures that each if statement has a corresponding else or else if, maintaining logical flow.
• Misaligned Structures: Detects scenarios where an else might not align with its intended if, potentially leading to logical errors.

By leveraging stacks, compilers can systematically verify that each opening construct has a corresponding closing construct, thereby ensuring code reliability and correctness.

Example: Syntax Parsing Using a Stack

Code Snippet:

def validate_syntax(code):
    stack = []
    for token in code.split():
        if token == "if":
            stack.append(token)
        elif token == "else":
            if not stack or stack[-1] != "if":
                return "Syntax Error: Unmatched 'else'"
            stack.pop()
    return "Valid Syntax" if not stack else "Syntax Error: Unmatched 'if'"

# Test Cases
print(validate_syntax("if if else else"))  # Valid
print(validate_syntax("if else else"))     # Error
print(validate_syntax("if if else"))       # Error

Output:

Valid Syntax
Syntax Error: Unmatched 'else'
Syntax Error: Unmatched 'if'

Explanation:

• The function scans the code and pushes if onto the stack.
• When encountering else, it checks if an if exists at the top.
• If else appears without a matching if, or if remains unmatched, a syntax error is returned.
• A balanced structure ensures valid syntax, commonly used in compilers for parsing nested conditions.

Also Read:  A Guide on Python String Concatenation

10. Resource Management

In resource management, stacks play a pivotal role in ensuring efficient allocation and deallocation of resources, adhering to the Last In, First Out (LIFO) principle. This methodology is particularly evident in various computing applications where resources are handled systematically.

• File Operations: When a program opens multiple files, each file handle is pushed onto a stack. Upon completion, file handles are popped off in reverse order, ensuring that the most recently opened file is closed first. This approach prevents resource leaks and maintains system stability.
• Network Connections: In managing multiple network connections, especially in server environments, stacks help track active connections. The most recent connection is pushed onto the stack, and upon termination, it pops off, ensuring proper closure and resource deallocation.

This stack-based management is vital in finance for transaction processing, healthcare for managing patient records, and technology for memory allocation.

Also Read: Importance of File Handling in C++ & How To Do It

11. Backtracking Algorithms

Backtracking algorithms utilize stacks to explore possible solutions by making choices, and if a path leads to a dead end, they backtrack to previous decisions to try alternative options. This method is particularly effective in solving problems like mazes and Sudoku puzzles.

Maze Solving with Depth-First Search (DFS):

In maze-solving, DFS employs a stack to navigate through the labyrinth:

• Push: Starting at the initial cell, it pushes the current position onto the stack.
• Explore: Moves to an adjacent unvisited cell, pushing each new position onto the stack.
• Backtrack: Upon reaching a dead end (a cell with no unvisited neighbors), it pops the stack to return to the previous position and explores alternative paths.

This process continues until the exit is found or all possibilities are exhausted.

Sudoku Solving with Backtracking:

In Sudoku, backtracking systematically fills empty cells:

• Attempt: Place a number in an empty cell.
• Validate: Checks if the number violates Sudoku rules.
• Proceed or Backtrack: If valid, moves to the next cell; if invalid, removes the number (backtracks) and tries the next possible number.

This approach ensures all potential solutions are explored efficiently.

Understanding these mechanisms highlights the practical applications of stacks in problem-solving scenarios.

Also Read: DFS (Depth First Traversal) in Data Structure: What is, Ordering & Applications

12. Solving Coding Problems Using Stack

Stacks are integral to solving various coding problems due to their Last In, First Out (LIFO) nature. This characteristic is particularly useful in scenarios where the most recent data needs to be accessed first. Several common coding challenges utilize stacks for efficient solutions:

• Next Greater Element: Involves finding the next greater number for each element in an array, efficiently solved using stacks.
• Valid Parentheses: Checks if an expression has balanced parentheses by pushing and popping brackets onto a stack.
• Stock Span Problem: Determines the number of consecutive days a stock's price was less than or equal to today's price, utilizing stacks for optimal computation.
• Balanced Expressions: Verifies if expressions with multiple types of brackets are balanced, employing stacks to ensure each opening bracket has a corresponding closing one.

These problems are prevalent in coding interviews and assessments, emphasizing the importance of mastering stack-based solutions. For instance, platforms like HackerEarth offer practice problems on stack basics, aiding in honing your skills.

Understanding stack examples in real life helps you see how LIFO works in daily activities. Now, explore the advantages and disadvantages of stacks in data structures.

Stack In Data Structure: Advantages And Disadvantages

Stacks are fundamental data structures that operate on the Last In, First Out (LIFO) principle, where the last element added is the first to be removed. This mechanism is prevalent in various computing processes and real-life scenarios. Understanding the advantages and disadvantages of stacks is crucial for their effective application.

Recognizing these aspects provides a balanced perspective on the utility of stacks.

Advantages of Stacks

Stacks offer several benefits that enhance data management and process execution:

• Efficient Data Management: Stacks follow the LIFO principle, making them ideal for scenarios where the most recent data is prioritized. For instance, in expression evaluation, the most recent operands are processed first.
• Memory Management: Stacks manage memory allocation and deallocation efficiently, especially in function call management. Local variables are stored on the stack, and memory is automatically reclaimed upon function exit.
• Simplified Implementation: Implementing stacks using arrays or linked lists is straightforward due to their linear structure. This simplicity facilitates quick integration into various applications.
• Backtracking Support: Stacks enable backtracking algorithms, such as solving mazes or puzzles, by storing previous states and allowing reversal of actions.

Also Read: What is DFS Algorithm? Depth First Search Algorithm Explained

While these advantages are significant, it's important to consider the limitations associated with stacks.

Disadvantages of Stacks

Despite their benefits, stacks have certain drawbacks:

• Limited Access: Stacks restrict access to only the top element, hindering retrieval or modification of elements deeper in the stack. This limitation can be problematic in applications requiring random access.
• Overflow Risk: Stacks have a fixed size, and exceeding this limit leads to stack overflow, causing program crashes or unexpected behavior. This issue is prevalent in environments with limited memory.
• Unsuitability for Certain Applications: Stacks are not ideal for applications requiring random data access or search operations, as they do not allow traversal beyond the top element.
• Debugging Challenges: Errors in stack operations, such as improper push or pop sequences, can be difficult to trace and debug, especially in complex applications.

Understanding these disadvantages is essential for making informed decisions about when to utilize stacks in your projects.

By carefully considering the advantages and disadvantages, you can effectively implement stacks in scenarios where their benefits outweigh their limitations.

How Can upGrad Help You Advance Your Career?

Understanding the Last In, First Out (LIFO) principle through real-life stack examples enhances your grasp of this fundamental data structure. To further develop your expertise, upGrad offers hands-on training, real-world projects, and personalized mentorship. 

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• AI-Powered Full Stack Development Course by IIITB
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