Elle #6
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Author
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Fixed. |
CheezItMan
reviewed
Oct 17, 2019
CheezItMan
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CheezItMan
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Nice work, you hit all the time and space complexities and solved both problems using a dynamic programming approach. Well done. The only criticism I could find was the use of p, s and n for variable names.
| # Time Complexity: O(n) where n is the length of the array | ||
| # Space Complexity: O(1) | ||
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| def max_sub_array(nums) |
| return string_solution[0...-1] | ||
| end | ||
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| def p(n, s) |
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Just noting the variable names are not meaningful here.
| return s[n-1] if s[n-1] | ||
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| if (n == 2) && !s[2-1] | ||
| s[2-1] = 1 |
| if (n == 2) && !s[2-1] | ||
| s[2-1] = 1 | ||
| else | ||
| s[n-1] = p(p(n - 1, s), s) + p(n - p(n - 1, s), s) |
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Nice both recursive and efficient solution.
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For max_subarray, my method is passing all of the provided tests but there's another case I wrote a test for and it's failing. Will try to debug tomorrow (Sunday).