Stacks: Tips and Tricks – Cracking the Coding Interview

Stacks: Tips and Tricks – Cracking the Coding Interview

Stacks are one of the most essential data structures that every software engineer should be familiar with, especially when preparing for coding interviews. The Last-In-First-Out (LIFO) principle of stacks makes them useful for various tasks, such as managing function calls, checking for balanced parentheses, evaluating expressions, and more.

In this article, we’ll explore tips and tricks to help you efficiently solve problems involving stacks in coding interviews. By understanding the inner workings of stacks and learning how to apply them strategically, you'll improve your ability to solve problems, manage data, and perform better in interviews.

What is a Stack?

A stack is a linear data structure that operates on the LIFO principle, meaning the last element added to the stack is the first one to be removed. Think of it like a stack of plates where you can only take the top plate off, and you add new plates to the top.

Stack Operations

The primary operations supported by a stack are:

• Push: Add an element to the top of the stack.
• Pop: Remove the element from the top of the stack.
• Peek (or Top): Get the value of the element at the top of the stack without removing it.
• IsEmpty: Check if the stack is empty.
• Size: Get the number of elements in the stack.

A stack can be implemented using an array, a linked list, or even Python’s built-in list data structure.

Stack Example in Python

class Stack:
    def __init__(self):
        self.stack = []
    
    def push(self, item):
        self.stack.append(item)
    
    def pop(self):
        if not self.is_empty():
            return self.stack.pop()
        else:
            return "Stack is empty"
    
    def peek(self):
        if not self.is_empty():
            return self.stack[-1]
        else:
            return "Stack is empty"
    
    def is_empty(self):
        return len(self.stack) == 0
    
    def size(self):
        return len(self.stack)

Example Usage

s = Stack()
s.push(10)
s.push(20)
s.push(30)

print(s.pop())  #  Output: 30
print(s.peek())  #  Output: 20
print(s.is_empty())  #  Output: False
print(s.size())  #  Output: 2

Tips and Tricks for Solving Problems Using Stacks

Now that you understand the basics of stacks, let’s dive into some useful tips and tricks that will help you excel in solving stack-based problems during your coding interviews.

1. Use Stacks for Problems Involving Last-In-First-Out Order

Stacks naturally solve problems that require processing items in reverse order, such as when dealing with function calls, backtracking, or undo mechanisms. If a problem requires you to “backtrack” through previous decisions or elements, a stack can be very helpful.

Tip:

• For problems where the order of elements matters, and you need to process the most recent element first (such as reversing or undoing actions), think of using a stack.

Example: Reversing a String Using a Stack

def reverse_string(s):
    stack = []
    for char in s:
        stack.append(char)
    
    reversed_string = ''
    while stack:
        reversed_string += stack.pop()
    
    return reversed_string

This uses the stack to reverse the string by first pushing each character onto the stack and then popping them off in reverse order.

2. Use Stacks to Handle Nested Structures

Stacks are great for problems involving nested structures, such as parentheses matching, balanced braces, or other similar patterns. The stack helps you "remember" where you are in the structure.

Tip:

• If the problem involves checking for matching parentheses, nested tags, or the validity of a structure that opens and closes (like HTML tags), a stack is a natural fit.

Example: Valid Parentheses

Given a string of parentheses, check if the parentheses are balanced.

def is_valid_parentheses(s):
    stack = []
    parentheses_map = {")": "(", "}": "{", "]": "["}
    
    for char in s:
        if char in parentheses_map:
            top_element = stack.pop() if stack else '#'
            if parentheses_map[char] != top_element:
                return False
        else:
            stack.append(char)
    
    return not stack

In this example, we use a stack to store the opening brackets and ensure that the correct corresponding closing bracket is encountered.

3. Simulate Recursion with a Stack

Recursion is essentially a form of stack-based operation, and in many cases, you can replace a recursive solution with an iterative one using a stack. This is particularly useful when dealing with deep recursion that might exceed the system’s recursion depth limit.

Tip:

• When a recursive problem involves traversing a tree, graph, or similar structure, consider converting the recursion to an iterative solution using a stack to avoid deep recursion.

Example: Iterative Depth-First Search (DFS)

DFS in a tree can be done recursively, but here's an iterative version using a stack:

def dfs_iterative(root):
    stack = [root]
    result = []
    
    while stack:
        node = stack.pop()
        result.append(node.val)
        if node.right:
            stack.append(node.right)
        if node.left:
            stack.append(node.left)
    
    return result

By using a stack, we simulate the recursive function call stack, processing nodes in a depth-first manner.

4. Use Two Stacks for Advanced Operations

In certain situations, you may need to use two stacks to solve a problem. This is often useful when you need to handle multiple stages of data processing, such as maintaining the order of elements or reversing the order.

Tip:

• When a problem requires you to perform operations like reversing an order or comparing data in two stages, using two stacks can be a powerful solution.

Example: Implement a Queue Using Two Stacks

A queue is a FIFO (First-In-First-Out) structure, but using two stacks, we can simulate this behavior.

class MyQueue:
    def __init__(self):
        self.stack1 = []
        self.stack2 = []
    
    def push(self, x):
        self.stack1.append(x)
    
    def pop(self):
        if not self.stack2:
            while self.stack1:
                self.stack2.append(self.stack1.pop())
        return self.stack2.pop()
    
    def peek(self):
        if self.stack2:
            return self.stack2[-1]
        return self.stack1[0]
    
    def empty(self):
        return not self.stack1 and not self.stack2

This simulates a queue by using two stacks to reverse the order of elements. The main operations—push, pop, and peek—can be implemented efficiently.

5. Optimize with Special Stack Variants

Sometimes, the problem requires you to keep track of additional information, such as the minimum element in a stack or the maximum value at any point. You can optimize the standard stack by maintaining additional stacks for auxiliary data, allowing you to solve problems more efficiently.

Tip:

• If the problem asks you to track the minimum or maximum value during stack operations, consider using an additional stack to track this information.

Example: Min Stack

Design a stack that supports push, pop, top, and get_min operations, where get_min retrieves the minimum element in the stack in constant time.

class MinStack:
    def __init__(self):
        self.stack = []
        self.min_stack = []
    
    def push(self, val):
        self.stack.append(val)
        if not self.min_stack or val <= self.min_stack[-1]:
            self.min_stack.append(val)
    
    def pop(self):
        val = self.stack.pop()
        if val == self.min_stack[-1]:
            self.min_stack.pop()
        return val
    
    def top(self):
        return self.stack[-1]
    
    def get_min(self):
        return self.min_stack[-1]

Here, the additional min_stack helps track the minimum value at each stage of the stack, allowing get_min to execute in constant time.

6. Track Order Using Stacks

In many problems, the order in which you add and remove items matters. Stacks are great for keeping track of the order in which items are processed.

Tip:

• When an order of operations matters (such as for undo operations or evaluating expressions), use a stack to store intermediate results or states.

Example: Evaluate Reverse Polish Notation (RPN)

Evaluate a mathematical expression in Reverse Polish Notation using a stack.

def eval_rpn(tokens):
    stack = []
    
    for token in tokens:
        if token in ["+", "-", "*", "/"]:
            b = stack.pop()
            a = stack.pop()
            if token == "+":
                stack.append(a + b)
            elif token == "-":
                stack.append(a - b)
            elif token == "*":
                stack.append(a * b)
            elif token == "/":
                stack.append(int(a / b))  #  Use integer division for truncation
        else:
            stack.append(int(token))
    
    return stack.pop()

In this case, the stack is used to hold the operands, and when an operator is encountered, we pop the operands off the stack, apply the operation, and push the result back onto the stack.

Conclusion

Stacks are an essential data structure to master for coding interviews. By understanding how to apply them to various problems—from handling nested structures to tracking values in real-time—you can significantly enhance your problem-solving abilities.

With the tips and tricks outlined in this article, you now have a stronger foundation in using stacks efficiently and effectively. Whether you're dealing with reversing data, evaluating expressions, or optimizing operations with auxiliary stacks, practicing stack-based problems will improve your coding skills and prepare you for even the toughest interview questions. Happy coding!