## Minimum Total Space Wasted With K Resizing Operations

You are currently designing a dynamic array. You are given a **0-indexed** integer array `nums`

, where `nums[i]`

is the number of elements that will be in the array at time `i`

. In addition, you are given an integer `k`

, the **maximum** number of times you can **resize** the array (to** any** size).

The size of the array at time `t`

, `size`

, must be at least _{t}`nums[t]`

because there needs to be enough space in the array to hold all the elements. The **space wasted** at time `t`

is defined as `size`

, and the _{t} - nums[t]**total** space wasted is the **sum** of the space wasted across every time `t`

where `0 <= t < nums.length`

.

Return *the minimum total space wasted if you can resize the array at most*

`k`

*times*.

**Note:** The array can have **any size** at the start and does** not **count towards the number of resizing operations.

**Example 1: Minimum Total Space Wasted With K Resizing Operations**

Input:nums = [10,20], k = 0Output:10Explanation:size = [20,20]. We can set the initial size to be 20. The total wasted space is (20 - 10) + (20 - 20) = 10.

**Example 2: Minimum Total Space Wasted With K Resizing Operations**

Input:nums = [10,20,30], k = 1Output:10Explanation:size = [20,20,30]. We can set the initial size to be 20 and resize to 30 at time 2. The total wasted space is (20 - 10) + (20 - 20) + (30 - 30) = 10.

**Example 3: Minimum Total Space Wasted With K Resizing Operations**

Input:nums = [10,20,15,30,20], k = 2Output:15Explanation:size = [10,20,20,30,30]. We can set the initial size to 10, resize to 20 at time 1, and resize to 30 at time 3. The total wasted space is (10 - 10) + (20 - 20) + (20 - 15) + (30 - 30) + (30 - 20) = 15.

**Constraints:**

`1 <= nums.length <= 200`

`1 <= nums[i] <= 10`

^{6}`0 <= k <= nums.length - 1`

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