DSA Module 9: Binary Tree Traversals & Depth

Why This Matters: Binary trees model hierarchical relationships (file systems, HTML DOM, decision trees).

## Tree Traversals & Recursion

Recursive height computation on Binary Trees.

```python
class TreeNode:
    def __init__(self, val=0, left=None, right=None):
        self.val = val
        self.left = left
        self.right = right

def max_depth(root: TreeNode) -> int:
    if not root:
        return 0
    return 1 + max(max_depth(root.left), max_depth(root.right))
```

MENTAL MODEL & MEMORY LAYOUT

BINARY TREE STRUCTURE:
          ( 3 )
         /     \
      ( 9 )   ( 20 )
              /    \
           ( 15 )  ( 7 )
Max Depth = 3

COMMON PITFALLS TO AVOID

Forgetting base case `if not root: return 0` causing AttributeError on null leaf node access.

Recursive Tree Depth Pattern

# Depth = 1 + max(left_depth, right_depth)

Computes maximum tree depth recursively in O(N) node evaluations.

CONCEPT MASTERY CHECKPOINT

Which tree traversal evaluates root first, then left subtree, then right subtree?

NEXT RECOMMENDED LESSON

DSA Module 10: Heaps & Priority Queues

Continue Path

Challenge: Calculate max depth of binary tree given depth array.

DSA Module 9: Binary Tree Traversals & Depth

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