package com.thealgorithms.dynamicprogramming; /** * Find the number of subsets present in the given array with a sum equal to target. * Based on Solution discussed on * StackOverflow(https://stackoverflow.com/questions/22891076/count-number-of-subsets-with-sum-equal-to-k) * @author Samrat Podder(https://github.com/samratpodder) */ public class SubsetCount { /** * Dynamic Programming Implementation. * Method to find out the number of subsets present in the given array with a sum equal to * target. Time Complexity is O(n*target) and Space Complexity is O(n*target) * @param arr is the input array on which subsets are to searched * @param target is the sum of each element of the subset taken together * */ public int getCount(int[] arr, int target) { /** * Base Cases - If target becomes zero, we have reached the required sum for the subset * If we reach the end of the array arr then, either if target==arr[end], then we add one to * the final count Otherwise we add 0 to the final count */ int n = arr.length; int[][] dp = new int[n][target + 1]; for (int i = 0; i < n; i++) { dp[i][0] = 1; } if (arr[0] <= target) dp[0][arr[0]] = 1; for (int t = 1; t <= target; t++) { for (int idx = 1; idx < n; idx++) { int notpick = dp[idx - 1][t]; int pick = 0; if (arr[idx] <= t) pick += dp[idx - 1][target - t]; dp[idx][target] = pick + notpick; } } return dp[n - 1][target]; } /** * This Method is a Space Optimized version of the getCount(int[], int) method and solves the * same problem This approach is a bit better in terms of Space Used Time Complexity is * O(n*target) and Space Complexity is O(target) * @param arr is the input array on which subsets are to searched * @param target is the sum of each element of the subset taken together */ public int getCountSO(int[] arr, int target) { int n = arr.length; int[] prev = new int[target + 1]; prev[0] = 1; if (arr[0] <= target) prev[arr[0]] = 1; for (int ind = 1; ind < n; ind++) { int[] cur = new int[target + 1]; cur[0] = 1; for (int t = 1; t <= target; t++) { int notTaken = prev[t]; int taken = 0; if (arr[ind] <= t) taken = prev[t - arr[ind]]; cur[t] = notTaken + taken; } prev = cur; } return prev[target]; } }