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| 1 | +package com.thealgorithms.slidingwindow; |
| 2 | + |
| 3 | +/** |
| 4 | + * The Sliding Window algorithm is used to find the minimum sum of a subarray |
| 5 | + * of a fixed size k within a given array. |
| 6 | + * |
| 7 | + * <p> |
| 8 | + * Worst-case performance O(n) |
| 9 | + * Best-case performance O(n) |
| 10 | + * Average performance O(n) |
| 11 | + * Worst-case space complexity O(1) |
| 12 | + * |
| 13 | + * This class provides a static method to find the minimum sum of a subarray |
| 14 | + * with a specified length k. |
| 15 | + * |
| 16 | + * @author Rashi Dashore (https://github.com/rashi07dashore) |
| 17 | + */ |
| 18 | +public final class MinSumKSizeSubarray { |
| 19 | + |
| 20 | + // Prevent instantiation |
| 21 | + private MinSumKSizeSubarray() {} |
| 22 | + |
| 23 | + /** |
| 24 | + * This method finds the minimum sum of a subarray of a given size k. |
| 25 | + * |
| 26 | + * @param arr is the input array where the minimum sum needs to be found |
| 27 | + * @param k is the size of the subarray |
| 28 | + * @return the minimum sum of the subarray of size k |
| 29 | + */ |
| 30 | + |
| 31 | + public static int minSumKSizeSubarray(int[] arr, int k) { |
| 32 | + if (arr.length < k) { |
| 33 | + return -1; // Edge case: not enough elements |
| 34 | + } |
| 35 | + |
| 36 | + int minSum; |
| 37 | + int windowSum = 0; |
| 38 | + |
| 39 | + // Calculate the sum of the first window |
| 40 | + for (int i = 0; i < k; i++) { |
| 41 | + windowSum += arr[i]; |
| 42 | + } |
| 43 | + minSum = windowSum; |
| 44 | + |
| 45 | + // Slide the window across the array |
| 46 | + for (int i = k; i < arr.length; i++) { |
| 47 | + windowSum += arr[i] - arr[i - k]; |
| 48 | + minSum = Math.min(minSum, windowSum); |
| 49 | + } |
| 50 | + return minSum; |
| 51 | + } |
| 52 | +} |
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