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Fire-Kalki-Tree-Practice #17
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Nice work Kalki, you hit the learning goals here. Well done. I had a few comments on space/time complexity, otherwise outstanding work.
# Time Complexity: O(log n) | ||
# Space Complexity: O(log n) | ||
def add(key, value = nil) |
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👍 Good use of default parameters. The space/time complexities are O(n) if the tree is unbalanced and O(log n) if the tree is balanced.
# Time Complexity: O(log n) | ||
# Space Complexity: O(l) | ||
def find(key) |
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👍 The space/time complexities are O(n) if the tree is unbalanced and O(log n) if the tree is balanced. I'm uncertain what O(l) is?
# Time Complexity: O(n) going through each node | ||
# Space Complexity: O(n) creating an array | ||
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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The space complexity is O(n) if the tree is unbalanced and O(log n) if the tree is balanced.
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