DFS with States
Prereq: Recursion, DFS on Tree
Let's reinforce our understanding of the concept of "states" with another example.
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
We use path
to keep track of the nodes we have visited so far to reach the current node and use it to construct our solution when we reach the leaf nodes.
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
17
1private 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 path.add(Integer.toString(root.val));
5 res.add(String.join("->", path));
6 return;
7 }
8 // DFS on each non-null child
9 for (Node<Integer> child : root.children) {
10 if (child != null) {
11 ArrayList<String> pathCopy = new ArrayList<>(path);
12 pathCopy.add(Integer.toString(root.val));
13 dfs(child, pathCopy, res);
14 }
15 }
16}
17
18public static List<String> ternaryTreePaths(Node<Integer> root) {
19 ArrayList<String> res = new ArrayList<>();
20 if (root != null) dfs(root, new ArrayList<String>(), res);
21 return res;
22}
23
1function 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 path.push(root.val);
5 const cur_path = path.join('->');
6 res.push(cur_path);
7 return;
8 }
9 // DFS on each non-null child
10 for (const child of root.children) {
11 if (child) {
12 const path_copy = Array.from(path);
13 path_copy.push(root.val);
14 dfs(child, path_copy, res);
15 }
16 }
17}
18
19function ternaryTreePaths(root) {
20 let res = [];
21 if (root) dfs(root, [], res);
22 return res;
23}
24
1void 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 == path.size() - 1) {
7 s += path[i];
8 } else {
9 s += path[i] + "->";
10 }
11 }
12 res.emplace_back(s);
13 return;
14 }
15 for (auto& child: root->children) {
16 if (child) {
17 std::vector<std::string> path_copy(path);
18 path_copy.emplace_back(std::to_string(root->val));
19 dfs(child, path_copy, res);
20 }
21 }
22}
23
24std::vector<std::string> ternary_tree_paths(Node<int>* root) {
25 std::vector<std::string> res;
26 if (root) dfs(root, {}, res);
27 return res;
28}
29
1private 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 path.Add(root.val.ToString());
7 res.Add(string.Join("->", path));
8 return;
9 }
10 // DFS on each non-null child
11 foreach (Node<int> child in root.children)
12 {
13 if (child != null)
14 {
15 List<string> pathCopy = new List<string>(path);
16 pathCopy.Add(root.val.ToString());
17 Dfs(child, pathCopy, res);
18 }
19 }
20}
21
22public static List<string> TernaryTreePaths(Node<int> root)
23{
24 List<string> res = new List<string>();
25 if (root != null) Dfs(root, new List<string>(), res);
26 return res;
27}
28
1func 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 path = append(path, strconv.Itoa(root.val))
5 *res = append(*res, strings.Join(path, "->"))
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}
20
Saving Space
In the recursive call in the previous solution, we create a new list each time we recurse with path + [root.val]
. This is not space-efficient because creating a new list involves allocating new space in memory and copying over each element. A more efficient method is to use a single list, path
, and push
and pop
according to the call stack.
Feel free to revisit the recursion section if you need a review of the call stack.
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