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July 17, 2022 15:38
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✨ Nice work Angela. I left some comments on time and space complexity, but overall it seems like you have a good understanding of linked lists.
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| # Space Complexity: ? | ||
| # Time Complexity: O(1) | ||
| # Space Complexity: O(1) | ||
| def get_first(self): |
| # Space Complexity: ? | ||
| # Time Complexity: O(1) | ||
| # Space Complexity: O(1) | ||
| def add_first(self, value): |
| # returns true if found, false otherwise | ||
| # Time Complexity: ? | ||
| # Space Complexity: ? | ||
| # Time Complexity: O(1) |
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⏱ Time complexity is O(n) since in the worst case the node with the value you are searching for will be the last node in the list, and you will have to iterate through every node in the list.
| # Space Complexity: ? | ||
| # Time Complexity: O(1) | ||
| # Space Complexity: O(1) | ||
| def search(self, value): |
| # Space Complexity: ? | ||
| # Time Complexity: O(n) | ||
| # Space Complexity: O(1) | ||
| def length(self): |
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| # Time Complexity: ? | ||
| # Space Complexity: ? |
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| # Time Complexity: ? | ||
| # Space Complexity: ? |
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| # Time Complexity: ? | ||
| # Space Complexity: ? |
| # returns the value at the middle element in the singly linked list | ||
| # Time Complexity: ? | ||
| # Space Complexity: ? | ||
| def find_middle_value(self): |
| # assume indexing starts at 0 while counting to n | ||
| # Time Complexity: ? | ||
| # Space Complexity: ? | ||
| def find_nth_from_end(self, n): |
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You could also take advantage of the get_at_index method you wrote
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