India - Water #32
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India - Water #32
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CheezItMan
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Apr 28, 2021
CheezItMan
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CheezItMan
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Nice work India, you hit the learning goals here. I left a few comments on space/time complexity, but otherwise this is all correct.
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| # Time Complexity: O(logn) | ||
| # Space Complexity: O(logn) | ||
| def add(key, value = nil) |
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👍 the method is Log n if the tree is roughly balanced.
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| # Time Complexity: O(logn) | ||
| # Space Complexity: O(logn) | ||
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| def find(key, current = @root) |
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👍 the method is Log n if the tree is roughly balanced.
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def inorder |
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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 postorder |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) | ||
| def height |
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👍 Because the recursion depth is dependent on the height of the tree it's O(log n) for space complexity for a balanced tree. It's O(n) if the tree isn't balanced.
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