Binary Tree Level Order Traversal
A medium-tier problem at 71% community acceptance, tagged with Tree, Breadth-First Search, Binary Tree. Reported in interviews at Gojek and 14 others.
Binary Tree Level Order Traversal is a medium-difficulty problem that shows up constantly in assessments from Apple, Microsoft, LinkedIn, and Bloomberg. You're given a tree and need to return nodes grouped by depth, left to right. The 70% acceptance rate is deceptive. Most candidates think recursion first, then hit the wall that depth tracking gets messy. BFS with a queue is the correct move, but the implementation trip-ups happen when you're live on screen and the depth-grouping logic isn't automatic. If this problem hits your assessment and you blank on the queue approach, StealthCoder surfaces the solution invisibly while you're screen-sharing.
Companies that ask "Binary Tree Level Order Traversal"
Binary Tree Level Order Traversal is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe trap is thinking recursively. Depth-First Search feels natural but you'll spend precious minutes managing a depth counter and restructuring your output. Breadth-First Search is the intended pattern here. Initialize a queue with the root, then process nodes level by level. For each level, you iterate through exactly as many nodes as are currently in the queue, collect their values, append left and right children back to the queue, and repeat. The key insight is that queue length at the start of each iteration equals the count of nodes at that depth. Common failures: forgetting to track when a level ends, adding children before popping parents, or returning a flat list instead of grouped levels. The topics are Tree, Breadth-First Search, and Binary Tree. StealthCoder is your hedge if the pattern doesn't click during your live OA.
Pattern tags
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Binary Tree Level Order Traversal recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Binary Tree Level Order Traversal interview FAQ
Is Binary Tree Level Order Traversal still asked at big tech companies?+
Yes. It appears in assessments from Microsoft, Apple, LinkedIn, Bloomberg, and TikTok regularly. Companies use it to filter for BFS understanding and basic tree manipulation. The 70% acceptance rate reflects that it's medium, not hard, but implementation speed under pressure matters.
What's the actual trick to this problem?+
The trick is recognizing that queue length at the start of each iteration tells you exactly how many nodes are at the current depth. Most candidates try to track depth manually or use recursion, both slower. Queue-based iteration, where you drain the current level before adding the next, is the pattern.
Should I use recursion or iteration?+
Iteration with a queue. Recursion requires passing depth as a parameter and managing a nested list structure, which is error-prone under time pressure. BFS with a deque is cleaner, faster to code, and matches the problem's intent.
How does this relate to the other BFS and Tree topics?+
This problem is a textbook Breadth-First Search applied to a Binary Tree. It's foundational. Once you own this pattern, shortest path in graphs, island counting, and other level-based traversals become muscle memory.
What do I code first if I'm stuck during the OA?+
Stub the queue initialization, the outer while loop, and the inner for loop that drains one level. Pseudocode those three blocks. Then fill in node value appending and child enqueueing. This structure forces correct logic and avoids off-by-one depth tracking.
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