LeetCode 3473: Sum of K Subarrays With Length at Least M Solution
Master LeetCode problem 3473 (Sum of K Subarrays With Length at Least M), a medium challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.
3473. Sum of K Subarrays With Length at Least M
Problem Explanation
Explanation:
To solve this problem, we can use dynamic programming with a sliding window approach. We will maintain a 2D dp array where dp[i][j] represents the maximum sum of j non-overlapping subarrays from nums[0] to nums[i], each with a length of at least m. We will iterate through the array and update the dp values accordingly.
- Initialize the dp array with size [nums.length][k+1].
- Iterate through the nums array.
- For each index i, iterate through the possible number of subarrays j (from 1 to k).
- Calculate the current subarray sum and update the dp array with the maximum sum.
- Return the maximum sum from dp[nums.length - 1][k].
Time Complexity: O(n * k) where n is the length of the nums array.
Space Complexity: O(n * k) for the dp array.
Solution Code
class Solution {
public int maxSumOfKSubarrays(int[] nums, int k, int m) {
int n = nums.length;
int[][] dp = new int[n][k + 1];
for (int i = 0; i < n; i++) {
for (int j = 1; j <= k; j++) {
int currSum = 0;
for (int x = i; x >= 0 && i - x + 1 >= m; x--) {
currSum = Math.max(currSum, x - 1 >= 0 ? dp[x - 1][j - 1] : 0);
dp[i][j] = Math.max(dp[i][j], currSum + Arrays.stream(Arrays.copyOfRange(nums, x, i + 1)).sum());
}
}
}
return dp[n - 1][k];
}
}Try It Yourself
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