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

The canonical fixture is 6 vertices [1..6] with undirected edges (1,2), (1,3), (2,4), (3,4), (4,5), (5,6) inserted in that order. The final adjacency list is {1: [2, 3], 2: [1, 4], 3: [1, 4], 4: [2, 3, 5], 5: [4, 6], 6: [5]}. This same graph drives graph-bfs, graph-dfs, and graph-shortest-path-bfs.

Basic Implementation

basic.pl
use strict; use warnings;
my @edges = ([1, 2], [1, 3], [2, 4], [3, 4], [4, 5], [5, 6]);
my %adj = ();
for my $e (@edges) {
	my ($u, $v) = @$e;
	push @{$adj{$u}}, $v;
	push @{$adj{$v}}, $u;
}
my @parts = ();
for my $v (sort { $a <=> $b } keys %adj) {
	push @parts, "$v: [" . join(", ", @{$adj{$v}}) . "]";
}
print "{" . join(", ", @parts) . "}\n";

Complexity

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

Implementation notes

  • Perl: a hash of array-refs maps each vertex to its neighbours; keys are sorted numerically before printing.
  • 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.