🎯 Breadth-First Search (BFS): Level-Order Traversal Pattern for Frontend Interviews
Category: dsa
Difficulty: hard
Interview Importance: 🔴 Critical — This technique appears in 40% of frontend coding interviews for tree/graph traversal, component hierarchy navigation, and shortest path problems. Essential for DOM manipulation and state management questions. 1️⃣ What is Breadth-First Search (BFS)? Breadth-First Search (BFS) is a graph/tree traversal algorithm that explores nodes level by level, visiting all neighbors at the current depth before moving to nodes at the next depth level. It uses a queue data structure to maintain the order of exploration. Visual Representation: [code example] Real-World Analogy: Think of BFS like ripples in water when you drop a stone. The ripples expand outward in concentric circles - first the innermost circle, then the next circle, and so on. Similarly, BFS explores all nodes at distance 1 from the start, then all nodes at distance 2, and so forth. This is exactly how Facebook's "People You May Know" suggestion works - it shows friends of friends (2 hops away) before showing friends of friends of friends (3 hops away). 2️⃣ Why Use BFS? / Why Does This Matter? Without BFS Benefit DFS might find longer path Optimal solution Level-order traversal Natural queue-based iteration Check all nodes randomly First found = nearest DOM tree traversal Iterative breadth-first May process out of order Correct execution order Aspect DFS Data Structure Stack/Recursion (LIFO) Level by level By edge weight Shortest Path ❌ No O(V + E) O((V + E) log V) Space Complexity O(h) height Shortest path, level-order Weighted shortest path Frontend Use Component tree, dependency resolution When to Use Which? [code example] 8️⃣ Common Interview Questions Q1: How do you implement BFS without recursion? Answer: BFS is naturally iterative using a queue. Recursion is more suited for DFS. [code example] Q2: How do you handle a disconnected graph with BFS? Answer: Run BFS from each unvisited vertex to cover all components. [code example] Q3: Find the right side view of a binary tree. ...