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Knowledge Base
dsaintermediate

Graph Algorithms: BFS, DFS, and Shortest Paths

Graph algorithms are a staple of technical interviews, testing your ability to solve complex problems using fundamental graph traversal and pathfinding techniques. Mastering these algorithms can set you apart in interviews, as they often form the backbone of more advanced problems you'll encounter. Understanding Breadth-First Search (BFS), Depth-First Search (DFS), and **Shortest Path Algo
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Graph algorithms are a staple of technical interviews, testing your ability to solve complex problems using fundamental graph traversal and pathfinding techniques. Mastering these algorithms can set you apart in interviews, as they often form the backbone of more advanced problems you'll encounter. Understanding Breadth-First Search (BFS), Depth-First Search (DFS), and Shortest Path Algorithms can be crucial to demonstrating your problem-solving skills.

Prerequisites

Before diving into graph algorithms, you should be familiar with:

  • Basic graph terminology (nodes, edges, directed vs. undirected graphs).
  • Data structures such as queues, stacks, and priority queues.
  • Complexity analysis (Big-O notation).

Breadth-First Search (BFS)

BFS is a graph traversal technique that explores nodes level by level, using a queue data structure to track exploration.

Python Implementation

from collections import deque

def bfs(graph, start):
    visited = set()
    queue = deque([start])
    
    while queue:
        node = queue.popleft()
        if node not in visited:
            print(node)
            visited.add(node)
            queue.extend(graph[node] - visited)

JavaScript Implementation

function bfs(graph, start) {
    let visited = new Set();
    let queue = [start];

    while (queue.length > 0) {
        le

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#dsa#graphs#bfs#dfs#dijkstra#shortest-path#topological-sort#interview-prep

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