FAANG Interview Graph Algorithms

🌐 Graph Preparation

How to Prepare Graph for FAANG Interview

Master graph concepts, algorithms, and interview patterns step-by-step.

Topic Graph | Difficulty Medium → Hard | Focus BFS / DFS / Shortest Path

Graph Roadmap

• FOUNDATION
• Introduction
• Graph Basics
• Representation
• CORE ALGORITHMS
• BFS / DFS
• Shortest Path
• MST
• ADVANCED
• Topological Sort
• SCC
• PRACTICE
• Problems
• Preparation Strategy

Intro Easy

Graph Overview

A graph consists of nodes (vertices) and edges connecting them. It is used to model real-world relationships like social networks and maps.

• Directed / Undirected
• Weighted / Unweighted

Step 1 Easy

Graph Basics

• Vertices & Edges
• Cycles & DAG
• Bipartite Graph

Step 2 Easy

Graph Representation

• Adjacency Matrix
• Adjacency List

Step 3 Medium

Traversal Algorithms

• BFS → shortest path (unweighted)
• DFS → recursion, cycle detection

Step 4 Hard

Shortest Path Algorithms

• Dijkstra
• Bellman-Ford
• Floyd-Warshall

Step 5 Hard

Minimum Spanning Tree

• Kruskal’s Algorithm
• Prim’s Algorithm

Advanced Medium

Topological Sorting

Used in DAG for dependency ordering.

Advanced Hard

Strongly Connected Components

Use Kosaraju or Tarjan algorithm.

Practice Medium

Important Problems

• Shortest Path
• Cycle Detection
• Number of Islands
• Topological Sort

Strategy Medium

Preparation Strategy

• Master BFS & DFS first
• Practice LeetCode problems
• Learn patterns (grid, shortest path)

Master graphs to crack FAANG interviews 🚀

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