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CheezItMan
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Sep 4, 2019
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You hit the learning goals here and even got Breadth-First-Search. I like how you used stacks & queues to do the iterative solutions (nonrecursive).
Nice work!
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| class TreeNode | |||
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| # Time Complexity: | ||
| # Space Complexity: | ||
| # Time Complexity: if well balanced, O(h) where h is the height of the tree |
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You could also say O(log n) if it's balanced, except that since you're going to visit each node in the tree, it has to be O(n)
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| # Time Complexity: | ||
| # Space Complexity: | ||
| # Time Complexity: if balanced, O(h) where h is the height of the tree |
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Since you have to visit each node to figure out the height, it's O(n) for time complexity. Space is different.
| stack = [] | ||
| output = [] | ||
| current = root | ||
| while current || !stack.empty? |
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It's neat how you used stacks here to avoid the recursive solution.
| return [] if @root.nil? | ||
| queue = [] | ||
| output = [] | ||
| queue.push(@root) |
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