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One for empty tree, one for tree_with_nodes
Add a test for the height method
CheezItMan
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CheezItMan
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Nicely done, all the methods work, but you do have issues with time/space complexity. Take a look at my comments and let me know what questions you have.
lib/tree.rb
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| # Time Complexity: O(logn) in worst case scenario | ||
| # Space Complexity: O(1) always just adding 1 new node | ||
| def add(key, value) |
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Actually O(log n) is the best and average case runtime.
Since you're doing recursion, you do incur some space complexity.
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@CheezItMan for the time complexity - would it be O(n) for worst case, and is that possible only if the tree is unbalanced?
| # Time Complexity: O(logn) since binary | ||
| # Space Complexity: O(1) since adding nothing new | ||
| def find(key) |
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Similar issues with time/space to add
| # Time Complexity: O(n) since going to each node once, backtracking but still backtracking a smaller number of times than there are nodes, so it depends on the number of nodes no matter what. | ||
| # Space Complexity: O(1) - nothing being made | ||
| def inorder |
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Space complexity is O(n) since you're building an array!
| # Time Complexity: same as inorder | ||
| # Space Complexity: same as inorder | ||
| def preorder |
| # Time Complexity: same as inorder | ||
| # Space Complexity: same as inorder | ||
| def postorder |
| # Time Complexity: O(n) since each node is visited once | ||
| # Space Complexity: O(1) since it doesn't make anything new | ||
| def height |
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The method works, but you have recursion and so some space complexity. Predictions?
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