What is the optimal time complexity of solving Tree Traversals?

The optimized solution achieves a time complexity of O(n) by using sorting, mathematical shortcuts, or hash table lookups.

What is the auxiliary space complexity for Tree Traversals?

The space complexity is O(1) since we only use a minimal/constant amount of extra memory for tracking variables (or auxiliary space if dynamic structures are allocated).

What are the typical edge cases we must handle in Tree Traversals?

Key edge cases include empty collections, negative or large bounds causing integer overflow, arrays with only one element, or inputs where target criteria are not met.

How can we optimize the brute force approach for Tree Traversals?

Brute force methods often inspect all possible combinations. We optimize this by sorting the input list to enable binary search, or tracking processed items in a set to avoid redundant nested loop lookups.

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DSA SectionMedium

Tree Traversals

Learn how to solve the 'Tree Traversals' problem. This detailed resource details brute force and optimized approaches.

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Problem Statement

Medium

Write a function get_tree_traversals(tree_arr) that takes an array representation of a binary tree tree_arr and returns a list of lists containing [inorder, preorder, postorder] traversals of the tree.

Constraints

•0 <= len(tree_arr) <= 1000

Examples

Example 1

Input

tree_arr = [1, None, 2, None, None, 3]

Output

[[1, 3, 2], [1, 2, 3], [3, 2, 1]]

Explanation

Inorder traversal visits left-root-right: [1, 3, 2]. Preorder visits root-left-right: [1, 2, 3]. Postorder visits left-right-root: [3, 2, 1].

Need a Hint?

Perform a recursive tree traversal (DFS) or level-order traversal (BFS) using a queue/stack.

Edge Cases to Watch

Empty list or null input variables
Single item lists/arrays
Extremely large input bounds causing integer or stack overflow

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