Binary Tree Level Order Traversal
Recognize the pattern
Brute force idea
The naive version of Binary Tree Level Order Traversal sounds like this: DFS with depth tracking, then sort by depth. Adds unnecessary sorting when BFS naturally processes by level. That direct path helps you understand the question, but it tends to treat every possibility as brand new instead of learning from earlier steps.
Better approach
A calmer way to see Binary Tree Level Order Traversal is this: BFS with a queue: process all nodes at the current depth, then move to the next level. Track the level size to know when one level ends and the next begins. The goal is not to be clever for its own sake, but to remember the one relationship that keeps the solution grounded as you move forward.
Key invariant
The truth you want to protect throughout Binary Tree Level Order Traversal is this: At the start of each level, the queue contains exactly the nodes at that depth. Processing them all before adding their children keeps levels separate. If that remains true after every update, the rest of the reasoning has a stable place to stand.
Watch out for
One easy way to drift off course in Binary Tree Level Order Traversal is this: Not tracking the level boundary — without knowing how many nodes are in the current level, you can't separate levels in the output. The fix is usually to return to the meaning of each move, not just the steps themselves.