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CheezItMan
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Feb 25, 2020
CheezItMan
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Nice work, you hit the basic learning goals, with some issues on space/time complexity. Check out my comments and let me know if you have any questions.
lib/tree.rb
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(1) | ||
| def add_helper(current_node, key, value) |
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The space complexity is O(log n) if the tree is balanced and O(n) if it's not.
lib/tree.rb
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(1) | ||
| def find_helper(current_node, key) |
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The space complexity is O(log n) if the tree is balanced and O(n) if it's not.
| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def inorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def postorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def preorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def height_helper(current_node) |
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The space complexity here depends on the recursive calls which depend on the height of the tree. So the space complexity is O(log n) for balanced trees and O(n) for unbalanced ones.
Otherwise the method is quite well done! 😃
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