Depth First Search Problems (338)

Depth-First Search (DFS) is one of the most fundamental traversal techniques used in data structures and algorithms. It explores a graph or tree by going as deep as possible along each branch before backtracking. DFS is commonly implemented using recursion or an explicit stack and is widely used to traverse Graph and Tree structures.

In coding interviews, DFS appears frequently because it naturally models many search and exploration problems. Whether you're checking connectivity in a graph, exploring all paths in a grid, or validating a binary tree property, DFS is often the simplest and most intuitive approach. Top tech companies expect candidates to be comfortable with DFS-based reasoning, especially when combined with Recursion, Backtracking, and other traversal strategies like Breadth-First Search.

As you practice DFS problems, you'll start to recognize common patterns that appear repeatedly in interview questions. Some of the most important DFS techniques include:

• Recursive traversal for trees and graphs
• Backtracking exploration for generating combinations or paths
• Visited set tracking to avoid cycles in graphs
• Connected component discovery in matrices or adjacency lists
• Path and state exploration for constraint-based problems

DFS is particularly useful when the solution requires exploring every possible path or deeply analyzing a structure before moving to the next branch. It powers algorithms for cycle detection, topological ordering, strongly connected components, and many grid-based search problems.

On FleetCode, you can master this technique through 333 carefully curated Depth-First Search problems. These exercises range from beginner tree traversals to advanced graph exploration challenges, helping you build strong intuition and interview-ready problem-solving skills.