Stop imagining.
Watch your code think.
Every concept below comes with step-by-step visual execution — run your own code, watch every variable change, every frame push, every pointer move. Real learning happens when you see it happen.
Build intuition, not just syntax
Run your own implementations. Watch every pointer, every node, every index change in real time.
Arrays
1D & 2D arrays, sliding window, prefix sum, two-pointer — every operation animated.
Linked Lists
Pointers made visual. Insertion, deletion, reversal, cycle detection — watch nodes link and unlink.
Stacks
LIFO made crystal clear. Push, pop, call stack behavior, balanced brackets and expression parsing.
Queues
FIFO, circular queues, priority queues, sliding window maximum — see the order of operations play out.
Hash Tables
Two Sum in O(1). Frequency counting, collision handling — the magic explained visually.
Binary Trees
Inorder, preorder, postorder traversals animated. BST insert, height, LCA — every recursive step shown.
Graphs
BFS and DFS animated node by node. Dijkstra, cycle detection, topological sort.
From "I memorized it" to "I understand it"
Write your own solution, watch it execute, see exactly where your logic diverges from the optimal path.
Recursion
Watch the call stack build and unwind frame by frame. Factorial, Fibonacci, backtracking — finally clicks.
Sorting Algorithms
Bubble, merge, quick, insertion — every swap and partition animated. Compare them side by side.
Dynamic Programming
Memoization vs tabulation. Coin change, knapsack, LCS — see subproblems get stored and reused.
Errors are lessons. See them happen.
Every error page shows the exact execution state at the moment your code breaks — not just a stack trace.
Don't memorize. Understand deeply.
Run your own solution to classic interview problems and see exactly what it does — that understanding holds up under pressure.
Top DSA Questions — FAANG
The 30 most commonly asked DSA problems at top companies, each with visual execution walkthroughs.
Recursion Interview Questions
Every classic recursion problem with call stack visualization. Factorial, Fibonacci, subsets, permutations.
Big O Notation — Visualized
See O(n), O(log n), O(n²) in execution. Understand why time complexity matters in your actual code.
BFS vs DFS — When to Use Which
Run both on the same graph and see exactly how the traversal order differs.
Two Sum — Brute Force to O(n)
See why O(n²) is slow and how the hash map approach gets to O(n).
Time Complexity Explained
How to analyze any algorithm's complexity — with real code showing execution count at each step.