Completed Trees-2

[Sanket-S-Kale]

No description provided.

[super30admin]

Construct Binary Tree from Inorder and Postorder Traversal (Problem1.py)

Strengths:

• Clear and comprehensive documentation with time/space complexity analysis
• Logical approach that correctly identifies root and splits arrays
• Good variable naming and code readability
• Proper handling of base cases

Areas for Improvement:

1. Replace inorder.index() with a hash map: This is the biggest optimization opportunity. Creating a dictionary mapping values to their indices in O(N) time once, then using O(1) lookups throughout recursion, would dramatically improve performance.

2. Use index-based access instead of array slicing: Instead of creating new arrays at each recursive call (inorder[:mid], postorder[:mid]), pass start and end indices to avoid O(N) copying overhead.

3. Consider using a class-level or global hash map: Store the value-to-index mapping outside the recursive function to avoid recreating it.

The core logic is correct, but optimizing the data access patterns would bring the solution closer to the reference implementation's efficiency.

VERDICT: NEEDS_IMPROVEMENT

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Sum Root to Leaf Numbers (Problem2.py)

Strengths:

• Excellent documentation with detailed comments explaining the algorithm logic
• Clear variable naming (result, helper, node, current)
• Correct handling of edge cases (null nodes, leaf nodes)
• Good explanation of time and space complexity in the docstring
• The example in comments (1->2->3) effectively illustrates how the number is built

Areas for Improvement:

• The solution is already well-optimized; no significant improvements needed
• Could optionally add type hints for better code documentation (e.g., def helper(node: Optional[TreeNode], current: int) -> None:)

VERDICT: PASS