patternjavaMinor
Performance analysis of 3 digits sum
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digitsanalysisperformancesum
Problem
I have a method that finds 3 numbers in an array that add up to a desired number.
I'm not sure about the big O of this method. I have a hard time wrapping my head around this right now. My guess is O(n2) or O(n2logn). But these are complete guesses. I can't prove this. Could someone help me wrap my head around this?
public static void threeSum(int[] arr, int sum) {
quicksort(arr, 0, arr.length - 1);
for (int i = 0; i j; k--) {
if ((arr[i] + arr[j] + arr[k]) == sum) {
System.out.println(Integer.toString(i) + "+" + Integer.toString(j) + "+" + Integer.toString(k) + "=" + sum);
}
}
}
}
}I'm not sure about the big O of this method. I have a hard time wrapping my head around this right now. My guess is O(n2) or O(n2logn). But these are complete guesses. I can't prove this. Could someone help me wrap my head around this?
Solution
The running time is O(n3). You have three nested loops:
Quicksort is generally O(n log n). So the total is O(n log n + 0.5 n × n × n), which is O(n3).
Since you took the trouble to sort the array, the innermost loop could be replaced by a binary search, which is O(log n). Therefore, an improved algorithm could work in O(n2 log n).
- Approximately n iterations of i
- For each i, approximately n iterations of j
- For each (i, j) pair, up to about n iterations of k. On average, it take just 0.5 * n iterations of k, but the constant factor doesn't matter.
Quicksort is generally O(n log n). So the total is O(n log n + 0.5 n × n × n), which is O(n3).
Since you took the trouble to sort the array, the innermost loop could be replaced by a binary search, which is O(log n). Therefore, an improved algorithm could work in O(n2 log n).
Context
StackExchange Code Review Q#46153, answer score: 7
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