Branches - Erika#46
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CheezItMan
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Sep 18, 2019
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Not bad. Check my implementation of Binary Search and see if you can see what's different in yours. Also check some of your methods for time and space complexity.
| # Time complexity: ? | ||
| # Space complexity: ? | ||
| # Time complexity: O(n) - constant | ||
| # Space complexity: O(n) |
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Since you are not building a new array this space complexity is O(1)
| # The restricted_array is terminated by 'nil' i.e. array[length] = nil | ||
| # Time complexity: ? | ||
| # Space complexity: ? | ||
| # Time complexity: O(n) - constant |
| def print_array(array) | ||
| raise NotImplementedError | ||
| index = 0 | ||
| array.length.times do |
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To use your length method this should be length(array).times
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| # For an unsorted array, searches for 'value_to_find'. | ||
| # Returns true if found, false otherwise. | ||
| # Time complexity: ? |
| # Space complexity: ? | ||
| def find_largest(array, length) | ||
| raise NotImplementedError | ||
| current = 0 |
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What if the array holds negative numbers?
I suggest starting current at array[0]
| # Space complexity: ? | ||
| def find_smallest(array, length) | ||
| raise NotImplementedError | ||
| current = array[0] |
| f_index = 0 | ||
| b_index = length - 1 | ||
| while f_index < b_index | ||
| array[f_index], array[b_index] = array[b_index], array[f_index] |
| # Returns true if found, false otherwise. | ||
| # Time complexity: ? | ||
| # Space complexity: ? | ||
| def binary_search(array, length, value_to_find) |
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This does may work, but it is not binary search. Check out my implementation of Binary Search
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| # For an array sorted in ascending order, searches for 'value_to_find'. | ||
| # Returns true if found, false otherwise. | ||
| # Time complexity: ? |
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