How do you solve N-ary Tree Preorder Traversal on LeetCode?

N-ary Tree Preorder Traversal (LeetCode #589) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Understanding tree traversal patterns is crucial for solving tree-related problems.

What is the brute force solution for N-ary Tree Preorder Traversal?

The brute force approach for N-ary Tree Preorder Traversal is Brute Force, with O(n²) time complexity and O(1) space complexity. In the brute-force approach, we can perform a depth-first search (DFS) recursively. We traverse each node and collect values in a list as we go, but this can lead to redundant traversals. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve N-ary Tree Preorder Traversal?

N-ary Tree Preorder Traversal uses the following concepts: Stack, Tree, Depth-First Search. The recommended patterns to study are: Depth-First Search (DFS), Stack.

What are the interview tips for N-ary Tree Preorder Traversal?

Always clarify if the tree can be empty and how you should handle that case. Explain your thought process while coding to demonstrate your understanding. Practice both recursive and iterative approaches, as interviewers may ask for both.

What are common mistakes when solving N-ary Tree Preorder Traversal?

Not considering edge cases such as an empty tree. Confusing the order of children when pushing to the stack.

#589

N-ary Tree Preorder Traversal

Easy

StackTreeDepth-First SearchDepth-First Search (DFS)Stack

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal solution uses an iterative approach with a stack, which allows us to avoid the overhead of recursive function calls and manage the traversal explicitly.

⚙️

Algorithm

3 steps

1Step 1: Initialize a stack and push the root node onto it.
2Step 2: While the stack is not empty, pop the top node, add its value to the result list.
3Step 3: Push all children of the popped node onto the stack in reverse order.

solution.py17 lines

1# Full working Python code
2class Node:
3    def __init__(self, val=None, children=None):
4        self.val = val
5        self.children = children if children is not None else []
6
7class Solution:
8    def preorder(self, root):
9        if not root:
10            return []
11        result = []
12        stack = [root]
13        while stack:
14            node = stack.pop()
15            result.append(node.val)
16            stack.extend(reversed(node.children))
17        return result

ℹ

Complexity note: The optimal solution runs in linear time because we visit each node exactly once, and the space complexity is linear due to the stack storing nodes.

1Understanding tree traversal patterns is crucial for solving tree-related problems.
2Iterative solutions often provide better performance and avoid stack overflow issues with deep recursion.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.