A Graph is one of the most important data structures in computer science, used to represent relationships between objects. It consists of vertices (nodes) connected by edges, making it ideal for modeling networks such as social connections, road maps, dependencies between tasks, and communication systems. Because of its flexibility, graph-based problems frequently appear in coding interviews at top tech companies.
Many interview problems revolve around exploring or analyzing graphs efficiently. Core traversal techniques like Breadth-First Search and Depth-First Search form the foundation for solving most graph problems. These techniques help detect cycles, explore connected components, and compute distances between nodes. Advanced patterns build on these basics, including shortest path algorithms such as Shortest Path and connectivity approaches like Union Find.
While practicing graph problems, you'll commonly encounter patterns such as:
Mastering graph algorithms not only improves problem-solving skills but also prepares you for real-world systems involving networks, scheduling, and large-scale data relationships. The 152 practice problems in this section will help you build intuition and confidence step by step.
Helps understand indexing, adjacency lists, and storing graph relationships efficiently.
Essential for implementing level-order traversal used in many graph algorithms like BFS.
Useful for solving connectivity problems, cycle detection, and algorithms like minimum spanning tree.
A core traversal strategy used for exploring graphs, detecting cycles, and finding connected components.
Fundamental graph traversal used for shortest paths in unweighted graphs and level-based exploration.
| Status | Title | Video | Leetcode | Solve | Difficulty | Companies | Topics |
|---|---|---|---|---|---|---|---|
| 997. Find the Town Judge | Solve | Easy | Adobe+3 | ||||
| 1791. Find Center of Star Graph | Solve | Easy | Microsoft | ||||
| 1971. Find if Path Exists in Graph | Solve | Easy | Amazon+2 |
Start Easy, progress to Hard.
Frequently appear alongside Graph.
Common questions about Graph.
A graph is a data structure made of nodes (vertices) connected by edges. It is commonly used to represent relationships such as networks, dependencies, or routes between locations.
They can seem complex at first because graphs model many scenarios. However, once you master traversal patterns and common representations like adjacency lists, most problems become much easier to approach.
Key algorithms include BFS, DFS, Dijkstra's algorithm, topological sort, and union-find based connectivity techniques. These form the backbone of most graph interview questions.
Graph problems test your ability to model relationships and apply traversal algorithms like BFS and DFS. Many real-world systems such as routing, recommendations, and scheduling rely on graph concepts.
Practicing 100+ graph problems across patterns like traversal, shortest paths, and connectivity is ideal. This helps you recognize problem patterns quickly during interviews.