Complete DP-3

[satish-paraddi]

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[super30admin]

Minimum Falling Path Sum (Problem_1.py)

It appears you submitted the solution for the wrong problem. The file is named Problem_1.py and contains a deleteAndEarn method, which solves LeetCode 740 "Delete and Earn," not LeetCode 931 "Minimum Falling Path Sum."

To correct this:

1. Re-read the problem carefully: The input is a 2D matrix (n×n), and you need to find the minimum sum path from top to bottom where each step moves to one of three positions in the next row.
2. Approach: Use bottom-up dynamic programming. Create a DP array where dp[i][j] represents the minimum falling path sum ending at cell (i, j). For each cell, dp[i][j] = matrix[i][j] + min(dp[i-1][j-1], dp[i-1][j], dp[i-1][j+1]) (handling boundary cases).
3. Answer: Return the minimum value in the last row of the DP array.
4. Time complexity target: O(n²) for an optimal solution.

Please resubmit with the correct solution for "Minimum Falling Path Sum."

VERDICT: NEEDS_IMPROVEMENT

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Delete and Earn (Problem_2.py)

It appears that you have submitted a solution for a different problem ("Minimum Falling Path Sum") instead of the assigned problem ("Delete and Earn").

To correctly solve "Delete and Earn":

1. Understand the problem: You need to pick numbers from an array, earn points equal to the picked number, and then all occurrences of num-1 and num+1 are also deleted.
2. Key insight: This problem is equivalent to the "House Robber" problem. If you create an array where arr[i] represents the total points you would earn by picking all occurrences of number i, then you need to find the maximum sum of non-adjacent elements in this array.
3. Approach:
   • First, find the maximum value in nums to determine the size of your counting array.
   • Create an array points where points[i] = sum of all is in nums.
   • Use DP: dp[i] = max(dp[i-1], points[i] + dp[i-2]).
4. Test your solution: Make sure your function signature matches deleteAndEarn(nums: List[int]) -> int.

Please re-implement the solution for the correct problem.

VERDICT: NEEDS_IMPROVEMENT