Learn Stack data structures in 10 minutes
Channel: Bro Code
Full video link:
https://www.youtube.com/watch?v=KInG04mAjO0Data Structure • easy
Stack is LIFO (last-in, first-out). The newest item is always removed first.
It maps naturally to nested structure handling: expressions, undo history, recursion simulation, and syntax validation.
When a problem needs 'most recent unresolved item', stack is usually the right fit.
Typical Complexity Baseline
| Metric | Value |
|---|---|
| Push/pop/top | O(1) |
Prefer video learning? This explainer gives a quick visual walkthrough of the core idea before you dive into the detailed sections below.
Learn Stack data structures in 10 minutes
Channel: Bro Code
Full video link:
https://www.youtube.com/watch?v=KInG04mAjO0Learn the core building blocks and terminology in one place before comparisons, so the mechanics are clear and duplicates are removed.
Top
What it is: Current most recent element.
Why it matters: Top is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Push
What it is: Insert new item on top.
Why it matters: Push is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Pop
What it is: Remove and return top item.
Why it matters: Pop is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Peek
What it is: Read top item without removal.
Why it matters: Peek is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Monotonic invariant
What it is: Optional ordering rule used in many optimization problems.
Why it matters: Monotonic invariant is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
LIFO
What it is: Last item added is first item removed.
Why it matters: Last item added is first item removed. In Stack (LIFO), this definition helps you reason about correctness and complexity when inputs scale.
Monotonic Stack
What it is: Stack that stays increasing/decreasing to optimize comparisons.
Why it matters: Stack that stays increasing/decreasing to optimize comparisons. In Stack (LIFO), this definition helps you reason about correctness and complexity when inputs scale.
Sentinel
What it is: Dummy value to simplify boundary handling.
Why it matters: Dummy value to simplify boundary handling. In Stack (LIFO), this definition helps you reason about correctness and complexity when inputs scale.
Underflow
What it is: Pop/peek attempted on empty stack.
Why it matters: Pop/peek attempted on empty stack. In Stack (LIFO), this definition helps you reason about correctness and complexity when inputs scale.
Call stack
What it is: Runtime-managed stack of active function frames.
Why it matters: Runtime-managed stack of active function frames. In Stack (LIFO), this definition helps you reason about correctness and complexity when inputs scale.
This walkthrough connects the core concepts of Stack (LIFO) into one end-to-end execution flow.
Step 1
Current most recent element.
Before
Stack top
After
Stack top
Transition
Why this step matters: Top is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Step 2
Insert new item on top.
Before
Stack top
After
Stack top
Transition
Why this step matters: Push is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Step 3
Remove and return top item.
Before
Input: "()
After
Transition
Why this step matters: Pop is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
Step 4
Read top item without removal.
Before
After
Transition
Why this step matters: Peek is a required building block for understanding how Stack (LIFO) stays correct and performant on large inputs.
vs Queue
When to choose this: Choose stack when most-recent-first semantics are required.
Tradeoff: Queue is better for first-in-first-out processing.
vs Recursion
When to choose this: Choose explicit stack when recursion depth may exceed safe limits.
Tradeoff: Recursion can be cleaner for tree-like code.
vs Array scan
When to choose this: Choose stack when unresolved prior states must be revisited.
Tradeoff: Simple scan is better when no backtracking state is needed.
Compiler and parser stacks track nested syntax while converting source code into internal representations.
Takeaway: Nested language constructs map directly to stack operations.
Figma
Undo/redo stacks maintain operation history for interactive editing sessions.
Takeaway: LIFO behavior provides intuitive user-facing history controls.
Browsers
JavaScript engines and layout systems track nested execution and traversal states with stack structures.
Takeaway: Stacks are foundational for runtime correctness.
Push open brackets, pop on close bracket, and ensure expected pair type.
Complexity: Time O(n), Space O(n)
Valid parentheses with stack
function isValidParentheses(text: string): boolean {
const stack: string[] = []
const expectedOpenByClose: Record<string, string> = { ')': '(', ']': '[', '}': '{' }
for (const char of text) {
if (char === '(' || char === '[' || char === '{') {
stack.push(char)
continue
}
const expectedOpen = expectedOpenByClose[char]
if (!expectedOpen) continue
if (stack.pop() !== expectedOpen) return false
}
return stack.length === 0
}
Use these signals to decide if this data structure/algorithm is the right fit before implementation.
O(1) operations.| # | Problem | Difficulty | Typical Complexity |
|---|---|---|---|
| 1 | Valid Parentheses | Easy | O(n) |
| 2 | Implement Stack using Queues | Easy | O(n) worst push |
| 3 | Min Stack | Medium | O(1) ops |
| 4 | Evaluate Reverse Polish Notation | Medium | O(n) |
| 5 | Daily Temperatures | Medium | O(n) |
| 6 | Car Fleet | Medium | O(n log n) |
| 7 | Largest Rectangle in Histogram | Hard | O(n) |
| 8 | Trapping Rain Water | Hard | O(n) |
| 9 | Basic Calculator | Hard | O(n) |
| 10 | Remove K Digits | Hard | O(n) |