Lab Index
Full listData Structures
- Singly Linked List
- Doubly Linked List
- Circular Linked List
- Circular Doubly Linked List
- Stack Visualization
- Queue Visualization
- Circular Queue
- Deque Visualization
- Priority Queue
- Binary Tree
- Binary Search Tree
- AVL Tree
- Red Black Tree
- Segment Tree
- Fenwick Tree
- Trie Visualization
- Heap Tree
- Hash Table
- Collision Resolution
- Linear Probing
- Chaining Visualization
- LRU Cache
- Skip List
- Disjoint Set Union
- Bloom Filter
- Sparse Table
Sorting Algorithms
Searching Algorithms
Recursion & Backtracking
Dynamic Programming
Pathfinding & Grid Search
Operating Systems
Computer Networking
Databases & Indexing
Compiler Design
Machine Learning
Web Development
System Design
Stack Visualization Visualizer
Push, pop, and examine LIFO element structures on an interactive memory stack.
New here? Here's how this lab works
Set your data & press Play — the canvas animates each step.
Follow the code in the tracer — the running line is highlighted live.
Go deeper with the Theory, Complexity & Interview Tips tabs.
Visualizer Canvas
Simulation initialized. Choose settings and click Play to start.
Execution Code Tracer
Ready// Visualizer code loading...Algorithmic Overview
Use the controls on the left to generate data and step through the algorithm. Watch how each element moves and compares — the Execution Code Tracer above highlights the exact line running at every step, so you can connect the animation to the code.
Switch languages (JS, Python, Java, C++) to see the same logic expressed in each, and open the Complexity and Interview Tips tabs for performance analysis and common questions.
Big O Performance Summary
| Case | Complexity |
|---|---|
| Best Time | O(N) |
| Average Time | O(N²) |
| Worst Time | O(N²) |
| Space Complexity | O(1) |
Invariants & Stability
Time complexity describes how the number of operations grows with the input size N, while space complexity tracks the extra memory used. Step through the visualizer to see where the work happens.
Key Interview Questions
Be ready to explain this technique in your own words: what problem it solves, its time and space complexity, and when you'd choose it over an alternative. Practice tracing it by hand on a small input — exactly what the visualizer animates here.
Pseudocode Representation
// Pseudocode goes here...
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