Build a Graph as an Adjacency List

Represent an undirected graph as a per-vertex list of neighbours. For every edge (u, v), append v to adj[u] and u to adj[v]. Neighbour lists keep insertion order so the graph is a stable, deterministic fixture for the search lessons.

Algorithm

Basic Implementation

basic.rs

use std::collections::BTreeMap;
fn main() {
	let edges = [(1, 2), (1, 3), (2, 4), (3, 4), (4, 5), (5, 6)];
	let mut adj: BTreeMap<i32, Vec<i32>> = BTreeMap::new();
	for &(u, v) in edges.iter() {
		adj.entry(u).or_insert_with(Vec::new).push(v);
		adj.entry(v).or_insert_with(Vec::new).push(u);
	}
	let mut parts: Vec<String> = Vec::new();
	for (v, nbrs) in &adj {
		let items: Vec<String> = nbrs.iter().map(|n| n.to_string()).collect();
		parts.push(format!("{}: [{}]", v, items.join(", ")));
	}
	println!("{{{}}}", parts.join(", "));
}

The graph fixture is pinned once, then the adjacency list writes each undirected edge in both directions.

Step 1 - Pinned graph fixture

The six vertices and six undirected edges are the shared fixture for BFS and DFS.

Step 2 - Final adjacency list

Each row lists neighbours in the same insertion order used by the lesson.

Complexity

Build: O(V + E)
Space: O(V + E)

Implementation notes

Rust: a BTreeMap<i32, Vec<i32>> keeps vertices sorted; entry().or_insert_with appends neighbours in edge order.
The replay shows the adjacency list after each edge is added, matching the lesson spec.

adjacency list Each edge adds two directed entries, one in each direction.