LeetCode 3196: Maximize Total Cost of Alternating Subarrays Solution

Master LeetCode problem 3196 (Maximize Total Cost of Alternating Subarrays), 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.

3196. Maximize Total Cost of Alternating Subarrays

Medium

Array Dynamic Programming

Problem Explanation

Explanation:

To solve this problem, we need to find the maximum total cost of splitting the array into subarrays. We can observe that the cost of each subarray depends on the sum of its elements with alternating signs. Hence, we need to find the optimal way to split the array such that the total cost is maximized.

Initialize variables to keep track of the current subarray's start index, previous element, and total cost.
Iterate through the array and calculate the cost of the current subarray.
Update the total cost if the current subarray's cost is greater.
Continue iterating and updating the subarray until we reach the end of the array.
Return the maximum total cost calculated.

Time Complexity: O(n) where n is the length of the input array. Space Complexity: O(1) as we are using constant extra space.

Solution Code

class Solution {
    public int maxTotalCost(int[] nums) {
        int start = 0;
        int prev = nums[0];
        int totalCost = 0;

        for (int i = 1; i < nums.length; i++) {
            int currCost = prev - nums[i];
            if (currCost > 0) {
                totalCost += currCost;
            } else {
                start = i;
            }
            prev = nums[i] * (i - start) - prev;
        }

        return totalCost;
    }
}

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