Ringo - Earth #3
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CheezItMan
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Apr 28, 2021
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| // Time Complexity: O(n*m log m) where n is the length of strings and | ||
| // m is the length of the longest string in the strings array. | ||
| // The for loop will run n times. Nested inside of that loop is a | ||
| // sort function that will be O(m log m) for strings of length m. | ||
| // Space Complexity: O(n). The sortedHash and the returned values array | ||
| // will increase in size proportionate to the size of the input. | ||
| function grouped_anagrams(strings) { |
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👍 , nice work on the space/time complexity
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| // Time Complexity: O(n log n). The controlling factor is the sort function | ||
| // which is O(n log n). | ||
| // Space Complexity: O(n). allHash and allKeys will both increase | ||
| // linear to the size of list. returnArray will increase with the size of k. | ||
| function top_k_frequent_elements(list, k) { |
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| // Time Complexity: O(1). The function does have a nested for loop. However, | ||
| // the input is always going to be a nine-by-nine board. The function | ||
| // will always have to look at, at most, 81 values one at a time. | ||
| // The time complexity does not change with the input but is constant. | ||
| // Space Complexity: O(1). The function makes 3 data structure that each, | ||
| // worst case scenario, end up holding the same amount of values as in the | ||
| // input. However, at most, this will be 81 values, 3 times -- a constant value. | ||
| function valid_sudoku(table) { |
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👍 Great work identifying the space/time complexity
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| function subgrid_helper(i, j) { |
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