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eric-andeen
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The code's fine, but by creating a hash, you're not really solving the problem as described. Try again to solve it without any additional allocations beyond the output array.
| # Time complexity: ? | ||
| # Space complexity: ? | ||
| # Time complexity: O(n+m) ~= O(n) where n is the length of the larger array because the code iterates through each item in both of the arrays. Looking up items in a hash table is O(1) time complexity; therefore the linear time complexity is dependent on the size of the larger array. | ||
| # Space complexity: O(n) - a new array is created to store intersecting values so space complexity is (worst-case) dependent on the length, n, of the array |
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Space complexity is O(n) for your solution - you're essentially making a whole copy of array1 in the hash. The assignment specifically says you should minimize space complexity. Can you do better than O(n)? Hint - the answer is yes.
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