Breadth-First Search (BFS)
Explore a graph level by level using a queue — shortest paths on unweighted graphs.
Breadth-First Search explores a graph outward in layers: it visits all neighbors of the start node first, then all of their unvisited neighbors, and so on. A queue holds the frontier — the nodes waiting to be processed — which is what gives BFS its level-by-level order.
Because it expands by distance, BFS finds the shortest path (in number of edges) on an unweighted graph. It is the backbone of flood fill, shortest-path-on-a-grid, and bipartite-checking problems.
AlgoLens renders the graph and the BFS queue together — you see which node comes out of the queue next and how the visited frontier grows, instead of guessing from printed output.
The code
#include <bits/stdc++.h>
using namespace std;
int main() {
int n, m;
cin >> n >> m;
vector<vector<int>> adj(n);
for (int i = 0; i < m; i++) {
int u, v;
cin >> u >> v;
adj[u].push_back(v);
adj[v].push_back(u);
}
vector<int> dist(n, -1);
queue<int> q;
q.push(0);
dist[0] = 0;
while (!q.empty()) {
int cur = q.front();
q.pop();
for (int nx : adj[cur]) {
if (dist[nx] == -1) {
dist[nx] = dist[cur] + 1;
q.push(nx);
}
}
}
for (int d : dist) cout << d << ' ';
cout << '\n';
return 0;
}
Now run your own Breadth-First Search (BFS)
AlgoLens traces your code — arrays, graphs, trees and recursion — from a real execution, so you see how it actually behaves, not a canned animation.
Paste your codeKeep going
Depth-First Search (DFS)
Go as deep as possible before backtracking — the recursion tree made visible.
Dijkstra's Algorithm
Shortest paths on a weighted graph — always expand the closest unfinished node.
Topological Sort
Order tasks so every dependency comes first — Kahn's algorithm with in-degrees.
Bubble Sort
The simplest sort — watch the largest value bubble to the end each pass.