DFS with States
Prereq: Recursion, DFS on Tree
In DFS, a state is information we pass from a parent call to a child call. In this article, the state is the path from the root to the current node.
Once you can carry this path state correctly, you can solve many backtracking problems by the same pattern: choose, recurse, undo.
Ternary Tree Paths
Given a ternary tree (each node of the tree can have up to three children), find all the root-to-leaf paths.

Try it yourself
Solution
Define dfs(node, path, res).
path stores the nodes on the current route from the root to node's parent. When we arrive at a leaf, we append node.val to that route, join with "->", and add the string to res.
For each non-null child, we recurse with the updated path that includes the current node value. This means each recursive call has exactly the state it needs: the route taken so far.
1def ternary_tree_paths(root):
2 # dfs helper function
3 def dfs(root, path, res):
4 # exit condition: when a leaf node is reached, append the path to the results
5 if all(c is None for c in root.children):
6 res.append('->'.join(path + [str(root.val)]))
7 return
8
9 # DFS on each non-null child
10 for child in root.children:
11 if child is not None:
12 dfs(child, path + [str(root.val)], res)
13
14 res = []
15 if root: dfs(root, [], res)
16 return res
171private static void dfs(Node<Integer> root, ArrayList<String> path, ArrayList<String> res) {
2 // exit condition: when a leaf node is reached, append the path to the results
3 if (root.children.size() == 0) {
4 ArrayList<String> fullPath = new ArrayList<>(path);
5 fullPath.add(Integer.toString(root.val));
6 res.add(String.join("->", fullPath));
7 return;
8 }
9 // DFS on each non-null child
10 for (Node<Integer> child : root.children) {
11 if (child != null) {
12 ArrayList<String> pathCopy = new ArrayList<>(path);
13 pathCopy.add(Integer.toString(root.val));
14 dfs(child, pathCopy, res);
15 }
16 }
17}
18
19public static List<String> ternaryTreePaths(Node<Integer> root) {
20 ArrayList<String> res = new ArrayList<>();
21 if (root != null) dfs(root, new ArrayList<String>(), res);
22 return res;
23}
241function dfs(root, path, res) {
2 // exit condition: when a leaf node is reached, append the path to the results
3 if (root.children.length === 0) {
4 const fullPath = [...path, root.val];
5 res.push(fullPath.join('->'));
6 return;
7 }
8 // DFS on each non-null child
9 for (const child of root.children) {
10 if (child) {
11 const path_copy = Array.from(path);
12 path_copy.push(root.val);
13 dfs(child, path_copy, res);
14 }
15 }
16}
17
18function ternaryTreePaths(root) {
19 let res = [];
20 if (root) dfs(root, [], res);
21 return res;
22}
231void dfs(Node<int>* root, std::vector<std::string> path, std::vector<std::string>& res) {
2 if (root->children.size() == 0) {
3 path.emplace_back(std::to_string(root->val));
4 std::string s = "";
5 for (int i = 0; i < path.size(); i++) {
6 if (i > 0) {
7 s += "->";
8 }
9 s += path[i];
10 }
11 res.emplace_back(s);
12 return;
13 }
14 for (auto& child: root->children) {
15 if (child) {
16 std::vector<std::string> path_copy(path);
17 path_copy.emplace_back(std::to_string(root->val));
18 dfs(child, path_copy, res);
19 }
20 }
21}
22
23std::vector<std::string> ternary_tree_paths(Node<int>* root) {
24 std::vector<std::string> res;
25 if (root) dfs(root, {}, res);
26 return res;
27}
281private static void Dfs(Node<int> root, List<string> path, List<string> res)
2{
3 // exit condition: when a leaf node is reached, append the path to results
4 if (root.children.Count == 0)
5 {
6 List<string> fullPath = new List<string>(path);
7 fullPath.Add(root.val.ToString());
8 res.Add(string.Join("->", fullPath));
9 return;
10 }
11 // DFS on each non-null child
12 foreach (Node<int> child in root.children)
13 {
14 if (child != null)
15 {
16 List<string> pathCopy = new List<string>(path);
17 pathCopy.Add(root.val.ToString());
18 Dfs(child, pathCopy, res);
19 }
20 }
21}
22
23public static List<string> TernaryTreePaths(Node<int> root)
24{
25 List<string> res = new List<string>();
26 if (root != null) Dfs(root, new List<string>(), res);
27 return res;
28}
291func dfs(root Node, path []string, res *[]string) {
2 // exit condition: when a leaf node is reached, append the path to results
3 if len(root.children) == 0 {
4 fullPath := append(path, strconv.Itoa(root.val))
5 *res = append(*res, strings.Join(fullPath, "->"))
6 return
7 }
8
9 // DFS on each non-null child
10 for _, child := range root.children {
11 dfs(child, append(path, strconv.Itoa(root.val)), res)
12 }
13}
14
15func ternaryTreePaths(root Node) []string {
16 var result []string
17 dfs(root, []string{}, &result)
18 return result
19}
20Saving Space
The first solution creates a new path object at each recursive step (path + [root.val] or equivalent). That is simple, but it allocates and copies repeatedly.
A more space-efficient version reuses one path list. Before going to a child, push root.val. After returning from that child, pop it. This keeps path synchronized with the call stack.
The rule is strict: every push must have one matching pop in the same stack frame. If you miss a pop, later branches will contain wrong nodes.
Compared with the basic DFS template, we surround each recursive call with push and pop to maintain path state correctly across sibling branches.
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