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CheezItMan
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Really nice work, you hit most of the learning goals here. Very elegantly written code. The only issue is with find, as it's not quite working, and you have some issues with space complexity, remember recursion incurs space complexity. Check out my comments and let me know any questions you have.
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(1) | ||
| def add(key, value) |
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This method is recursive so it's going to have some space complexity. What do you think it is?
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| until current.key == key | ||
| if current.key > key | ||
| current = current.left | ||
| else | ||
| current = current.right | ||
| end | ||
| end |
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What about if the key is not in the tree? What about when current is nil?
Suggested change
| until current.key == key | |
| if current.key > key | |
| current = current.left | |
| else | |
| current = current.right | |
| end | |
| end | |
| until current.key == key | |
| if current.key > key | |
| current = current.left | |
| else | |
| current = current.right | |
| end | |
| return nil if current.nil? | |
| end |
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(n) n represents the number of nodes in a tree | ||
| 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(1) | ||
| def height |
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Note that this is a recursive method so you're going to have space complexity due to the call stack.
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