🔥 “Stack Explained: The Secret Weapon Behind LeetCode Monotonic Problems”

Mastering Stack Data Structure – From Basics to LeetCode Practice

Stacks are one of the most fundamental data structures in computer science and play a critical role in problem-solving, algorithms, and real-world systems. In this post, I’ll …


This content originally appeared on DEV Community and was authored by M Umair Ullah

Mastering Stack Data Structure – From Basics to LeetCode Practice

Stacks are one of the most fundamental data structures in computer science and play a critical role in problem-solving, algorithms, and real-world systems. In this post, I’ll walk you through what a stack is, why we need it, important algorithms, and how I’m practicing LeetCode stack problems to master this concept. I’ll also share my GitHub repository link at the end where I upload all my practice codes.

📌 What is a Stack?

A stack is a linear data structure that follows the principle of LIFO (Last In, First Out).

  • Imagine stacking plates: you can only take out the plate on the top.
  • The same rule applies to a stack: Insertions (push) and deletions (pop) happen only at one end (top).

Basic Operations:

  1. push(x): Insert element x at the top.
  2. pop(): Remove the top element.
  3. top()/peek(): Get the top element without removing it.
  4. isEmpty(): Check if stack is empty.

⚡ Why Do We Need a Stack?

Stacks may sound simple, but they are powerful and used everywhere:

  • Expression Evaluation: Balanced Parentheses, Infix → Postfix conversion.
  • Backtracking: Undo/redo in editors, recursion call stack.
  • Monotonic Stack Problems: Next Greater Element, Stock Span, Daily Temperatures.
  • System Design: Function calls in memory are handled using a call stack.

🔑 Important Stack Problem References

Here are the must-practice problems (with links) that cover all the essential stack patterns:

🟢 Easy

🟡 Medium

đź”´ Hard

⏱️ Time & Space Complexity Analysis

Operation Time Complexity Space Complexity
Push O(1) O(1)
Pop O(1) O(1)
Peek/Top O(1) O(1)
Search O(n) O(1)
Next Greater Element / Daily Temperatures O(n) O(n)

👉 Most stack-based problems (like NGE, Daily Temperatures) are O(n) because each element is pushed and popped at most once.

📚 My LeetCode Practice Plan

To fully master stacks, I’m solving these problems step by step:

  1. Easy Level: Warm up with Valid Parentheses, Min Stack.
  2. Medium Level: Focus on monotonic stack problems (NGE, Daily Temperatures, Stock Span).
  3. Hard Level: Move on to Histogram and Matrix-based problems.

This ensures I cover all core algorithms involving stacks.

đź“‚ GitHub Repository

I’m uploading all my stack solutions (brute force + optimized stack approach) to my GitHub repo.

👉 Check it out here: My GitHub Repo – Stack Practice

✨ Conclusion

Stacks are simple but powerful. By practicing problems like Next Greater Element, Daily Temperatures, Histogram problems, you’ll not only master the stack but also build a strong foundation for advanced algorithms and interview prep.

💡 My approach: I’m practicing every problem type, pushing solutions to GitHub, and writing blogs to keep track of my journey.

🔥 If you’re also practicing, try out these problems, optimize your solutions, and let’s grow together!


This content originally appeared on DEV Community and was authored by M Umair Ullah


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