Binary Tree Level Order Traversal

Binary Tree Level Order Traversal

What is this problem about?

Binary Tree Level Order Traversal is the process of visiting nodes level by level, from top to bottom and left to right. Imagine you are scanning a tree horizontally. This "breadth-first" approach is distinct from "depth-first" searches like inorder or preorder. The goal of this coding problem is to return a list of lists, where each sub-list contains the values of nodes at a specific depth.

Why is this asked in interviews?

This is one of the most frequently asked questions in tech interviews at companies like Google, LinkedIn, and Uber. It tests your proficiency with the Breadth-First Search (BFS) interview pattern. Level order traversal is the foundation for solving more complex problems like finding the shortest path in a graph, implementing "connected components," or even simple tasks like finding the "right-side view" of a tree. Understanding how to manage a queue to process nodes in layers is a critical skill for any software engineer.

Algorithmic pattern used

The primary pattern here is the Breadth-First Search (BFS) using a Queue. You start by adding the root to the queue. While the queue isn't empty, you determine the number of nodes currently in the queue (this represents the current level's size), process that many nodes by adding their values to a temporary list and their children to the queue, and then move to the next level.

Example explanation

Consider this tree: A / B C / / D E F

1. Level 0: Queue = [A]. Result = [[A]].
2. Level 1: Pop A, add children B, C. Queue = [B, C]. Result = [[A], [B, C]].
3. Level 2: Pop B, add child D. Pop C, add children E, F. Queue = [D, E, F]. Result = [[A], [B, C], [D, E, F]]. The final output clearly separates the tree into its horizontal layers.

Common mistakes candidates make

A common pitfall is forgetting to capture the queue size at the start of each level's processing. If you just loop while the queue isn't empty and add children, you won't know where one level ends and the next begins. Another mistake is not handling the null/empty tree case at the very beginning.

Interview preparation tip

Mastering the "Queue with Size" variation of BFS is essential. It's a template that applies to dozens of tree and graph problems. When you see "level by level" or "shortest distance" in a problem description, your mind should immediately jump to this specific BFS structure.