## Problem Given a list of integers and K, partition it into exactly K non-empty contiguous subarrays. Minimize the difference between the maximum subarray sum and the minimum subarray sum across all K groups. ```python def split_integers(nums: list[int], k: int) -> tuple[list[list[int]], int]: # returns: (partition, max_sum - min_sum) pass def min_split_difference(nums: list[int], k: int) -> int: # returns: the minimum achievable difference pass ``` **Example:** ``` nums = [1, 2, 3, 4, 5], k = 2 # Best split: [1,2,3] sum=6, [4,5] sum=9 -> diff=3 # Or [1,2,3,4] sum=10, [5] sum=5 -> diff=5 min_split_difference([1,2,3,4,5], 2) -> 3 ``` ## Follow-ups 1. How does a DP formulation with states (index, groups_remaining) solve this? 2. What is the time complexity of your DP solution? 3. How would binary search on the answer simplify the problem (binary search on difference)? 4. Does the order of elements in the array matter? What if elements can be rearranged?

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Integers Split: Split an Array of Integers into K Groups with Minimum Sum Difference

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Problem Given a list of integers and K, partition it into exactly K non-empty contiguous subarrays. Minimize the difference between the maximum subarray sum and the minimum subarray sum across all K groups. Example: Follow-ups How does a DP formulation with states (index, groups_remaining) solve this? What is the time complexity of your DP solution? How would binary search on the answer simplify the problem (binary search on difference)? Does the order of elements in the array matter? What if el…

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It covers the following topics: Dynamic Programming, Phone, Binary Search, Coding, Arrays .

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Integers Split: Split an Array of Integers into K Groups with Minimum Sum Difference

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