Below is a pattern-focused breakdown of DFS, BFS, and Heap usage tailored for LeetCode-style problems. This is structured for pattern recognition → template → when to use → example problems.

DFS Patterns (Trees & Graphs)

Core Idea

• Go deep first, then backtrack
• Uses recursion (stack) or explicit stack
• Good for exploring all possibilities

Simple Traversal (Tree DFS)

Use When

• Visit all nodes
• Compute something (sum, depth, etc.)

Template

def dfs(node):

	if not node:
		return
		
	# process node
	
	dfs(node.left)
	dfs(node.right)

Variations

• Preorder → process before recursion
• Inorder → process between
• Postorder → process after

Problems

• Max Depth of Binary Tree
• Same Tree
• Subtree of Another Tree