implementing Merge Sort Optimization in Java - Unexpected Memory Consumption Increase
I'm following best practices but I've encountered a strange issue with I'm currently implementing an optimized version of the Merge Sort algorithm in Java, but I've run into a important scenario with memory consumption... My goal is to reduce the auxiliary space complexity, but it seems that the optimized version consumes more memory than expected. Here's the snippet of my implementation: ```java public class MergeSort { public void mergeSort(int[] array) { if (array.length < 2) { return; } int mid = array.length / 2; int[] left = Arrays.copyOfRange(array, 0, mid); int[] right = Arrays.copyOfRange(array, mid, array.length); mergeSort(left); mergeSort(right); merge(array, left, right); } private void merge(int[] array, int[] left, int[] right) { int i = 0, j = 0, k = 0; while (i < left.length && j < right.length) { if (left[i] <= right[j]) { array[k++] = left[i++]; } else { array[k++] = right[j++]; } } while (i < left.length) { array[k++] = left[i++]; } while (j < right.length) { array[k++] = right[j++]; } } } ``` While the algorithm sorts the input correctly, I noticed that for larger arrays (around 1 million integers), the JVM memory usage spikes significantly, peaking at about 3 times the initial allocated memory. I'm using JDK 17 and running on macOS Monterey, and I've tried various configurations. I've also attempted to implement in-place merging to mitigate this, but I need to seem to get it right without altering the algorithm's fundamental properties. When I run this with `-Xmx512m` as JVM arguments, I get an `OutOfMemoryError` on larger datasets. Is there a better way to handle the merging process or manage memory without reverting to the traditional merge sort? Any insights into how I can optimize this further would be greatly appreciated! This is happening in both development and production on Ubuntu 22.04. Thanks in advance! This is for a mobile app running on Windows 11. Any ideas how to fix this?