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22d4a No.1506

right now i was trying to wrap my head around the bfs (breadth-first search) for graphs or trees and stumbled upon this super clear tutorial. it walks you through each part of implementing bfs using java, ⚡and even includes some practical examples!

i found myself nodding along as if someone were explaining over a coffee break: "okay so we initialize the queue with our starting node," then they say something like "next up is adding neighbors to it" and i'm just thinking 'aha gotcha!'

the best part? there are actual code snippets! you can follow right along, see how each line fits into building your graph traversal. but hey guys - if anyone has a tip or an alternative approach for bfs in java that they've found to be even more efficient than this one. drop it here!

i hope some of y'all find as much clarity from reading through these examples and explanations

article: https://dev.to/rajesh1761/bfs-algorithm-in-java-step-by-step-tutorial-with-examples-6ld

22d4a No.1507

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>>1506
lowkey bfs in java is pretty straightforward when u get into it:
import Queue;public void bfs(Node root) { if (root null) return; // queue for node processing and marking as visited using a boolean array or set. Queue<Node> q = new LinkedList<>(); q. add(root); root. visited=true;  while (! q. isEmpty()) {  Node n=q. poll();   System. out. print(n. data + " "); /'' process the current vertex ''/ // Get all adjacent nodes of the dequeued node for (Node adj : getNeighborsList(q)) { if(! adj. isVisited) {/'' If not visited, mark it as true and enqueue ''/ q. add(adj); adj. visited=true; } }  }}

this covers a simple bfs traversal. remember to handle edge cases like null nodes or empty queues.

if youre working with graphs in java these days ⚡,
consider using the adjacency list representation for efficient neighbor lookups.
also, dont forget about cycle detection and how it can impact ur implementation ❤



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