Learn and practice the Tree Depth-First Search and Tree Breadth-First Search patterns to solve coding interview problems.

Grokking Grind 75 in Go: Mastery through Coding Patterns

Trees play a pivotal role in organizing hierarchical data, optimizing searches, and solving complex problems. In this module, we’ll learn to choose the appropriate tree for a given problem and apply the more appropriate of the two major traversal techniques, breadth-first or depth-first, to solve it.

Trees

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## Statement

Given a binary tree with $n$ nodes, return TRUE if it is #key# height-balanced: A binary tree is considered height-balanced if the difference between the heights of the two subtrees for each node is not more than 1. #key#. Otherwise, return FALSE.

> **Note:** The height of an empty tree is $0$.

**Constraints:**

* $1 \leq n \leq 500$
* $-10^4 \leq$ `Node.Data` $\leq 10^4$

Let's solve the Balanced Binary Tree problem using the Tree Depth-first Search pattern.

Tree Depth-first Search

Tree Breadth-first Search

Conclusion

Solution: Balanced Binary Tree

Statement