Big O exercise #26
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Big O exercise #26
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mmmaaatttttt
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Aug 1, 2017
| 5. `O(n + n + n + n)` | ||
| O(n) | ||
| 6. `O(1000 * log(n) + n)` | ||
| O(log(n)) |
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double check this one - which grows faster, log(n) or n?
| 7. `O(1000 * n * log(n) + n)` | ||
| O(n * log(n)) | ||
| 8. `O(2^n + n^2)` | ||
| O(n^2) |
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2^n grows faster than n^2, but i wouldn't sweat this one too much since we didn't talk about exponential growth in class.
| console.log(i); | ||
| } | ||
| } | ||
| Time: O(n) |
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double check your time complexity here. What's the largest number of operations that will be performed?
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