Graph traversal separates engineers who guess from engineers who build. Breadth-first search (BFS) and depth-first search (DFS) power everything from social network recommendations to web crawlers, yet most developers stop at textbook implementations. The linked Practice Graph Traversal Problems article teaches three specific techniques: iterative BFS for shortest paths in unweighted grids, recursive DFS for detecting cycles in directed graphs, and two-pointer state tracking for cloning complex linked structures with random pointers.
This content is for developers preparing for senior-level interviews, students moving beyond academic pseudocode, and professionals adding graph fluency to their toolkit. You'll learn to spot when a problem demands level-order traversal versus backtracking — a distinction that turns impossible-seeming challenges into clear code.
Below you'll find exercises that build from adjacency list basics to multi-source BFS and articulation points. Each problem reinforces the mental model: choose BFS when proximity matters, DFS when completeness matters. Master these, and you stop fearing graph interviews. Start with the featured article, then prove your traversal intuition on the problems that follow.
Practice graph traversal problems with our curated exercises. Master BFS, DFS, and advanced algorithms through hands-on coding challenges and solutions.