Visit a start vertex, then recurse into its first unvisited neighbour all the way down before backtracking. A visited set prevents revisiting, and neighbour insertion order fixes the visit sequence.

Algorithm

On the canonical 6-vertex graph from graph-adjacency-list, starting at vertex 1, the deterministic visit order is [1, 2, 4, 3, 5, 6]. Calls unwind 6 -> 5 -> 4 -> 3 -> 2 -> 1 after all vertices are visited.

Basic Implementation

Basic.java
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;

public class Basic {
    static Map<Integer, List<Integer>> adj = new LinkedHashMap<>();
    static Set<Integer> visited = new LinkedHashSet<>();
    static List<Integer> order = new ArrayList<>();

    static void dfs(int v) {
        visited.add(v);
        order.add(v);
        for (int nb : adj.get(v)) {
            if (!visited.contains(nb)) {
                dfs(nb);
            }
        }
    }

    public static void main(String[] args) {
        adj.put(1, List.of(2, 3));
        adj.put(2, List.of(1, 4));
        adj.put(3, List.of(1, 4));
        adj.put(4, List.of(2, 3, 5));
        adj.put(5, List.of(4, 6));
        adj.put(6, List.of(5));
        dfs(1);
        System.out.println(order);
    }
}

Complexity

  • Time: O(V + E)
  • Space: O(V) recursion depth

Implementation notes

  • Java: a static dfs(int v) method shares the visited LinkedHashSet and order list; recursion depth is bounded by V.
  • The replay shows the current vertex, the visited set, the running visit order, and the call stack after each entry, matching the lesson spec.
recursive descent Follow one branch to its end, then unwind and try the next neighbour.