Pick a problem, hit play, and actually see what the code is doing — on real trees, arrays, and graphs. 150+ problems from the most common interview patterns, broken down step by step so nothing feels like magic.
No more staring at code hoping it clicks. Watch every node visit, every comparison, every pointer shift play out on real data structures — right in front of you.
Each step highlights the exact line running. You see the code, you see what it does to the data structure — and suddenly the solution makes sense.
Recursion finally makes sense when you can see it. The stack grows as calls go deeper, then unwinds as values come back up. No more hand-tracing on paper.
Drop in trees, linked lists, arrays — or just sketch your approach freehand. Drag nodes around, edit values, jot notes next to your diagrams. Everything saves on its own.
Relink node 2 → node 3, then return head
The study loop that actually makes algorithms stick.
Give it a real shot — 20 to 30 minutes. Even if you don't crack it, the struggle is what makes the solution stick later.
Search for the problem, pick an algorithm, and step through it frame by frame. See every operation happen on the actual data.
Now that you've seen how it works, implement the solution from understanding — not memorization. That's where the real learning happens.
After a handful of problems, the same patterns keep showing up. Once you spot them, new problems stop feeling impossible.
150+ problems. Every major pattern. One step at a time.
Select an algorithm to visualize step-by-step
When you rotate an array right by k, you're taking the last k elements and moving them to the front, while shifting everything else back.
Instead of moving them one by one, we use reversal to flip the chunks into place.
This moves the elements that belong at the front (4, 5) to the front, and the elements that belong at the back (1, 2, 3) to the back. But both chunks are currently backwards.
The front chunk (5, 4) gets flipped back to its correct order (4, 5).
The back chunk (3, 2, 1) gets flipped back to its correct order (1, 2, 3). Done.
Think of it like exploring a map. You start with a small area you can reach. You look around, figure out the farthest spot you can get to next, then "jump" — expanding your reach.
Each jump opens up a new zone. You keep going until the end is inside your zone.
The outer loop handles jumps — each time it runs, you're making one jump.
The inner loop looks at every cell in your current zone and asks: "what's the farthest any of these can reach?"
L and R mark the edges of your current zone — everything between them is reachable with the current number of jumps.
Think of it like: "I can land on any of these spots right now."
Each cell in the zone is a launch pad. We check every one and remember whichever can reach the farthest: farthest = max(farthest, i + nums[i])
We don't care which cell was best — just how far the best one gets us. That becomes the right edge of our next zone.
After checking every cell in [L, R]:
L = R + 1 (new zone starts)The old zone fades out. The new, bigger zone lights up.
By always expanding to the farthest reachable point, you cover the most ground per jump. There's no scenario where a shorter jump now would save you jumps later.