add dp-3 solutions

[nikhylw]

No description provided.

[super30admin]

Least Falling Path Sum (min_failing_path.py)

Strengths:

1. Excellent use of dynamic programming - the bottom-up approach is more efficient than the reference's naive recursion
2. Clean, readable code with descriptive variable names
3. In-place modification of the matrix achieves O(1) space complexity
4. Correctly handles boundary conditions for edge columns
5. Well-commented with complexity analysis

Areas for Improvement:

1. The solution modifies the input matrix, which may not be allowed in some contexts. Consider creating a copy if immutability is required.
2. Could add a check for edge cases like empty matrix or single element matrix for robustness.

Comparison to Reference:
Your solution is significantly better than the reference solution in both time and space complexity. The reference solution has exponential time complexity due to naive recursion, while your solution achieves optimal O(n²) time. Similarly, your O(1) space usage beats the reference's O(n) recursion stack.

VERDICT: PASS

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Delete and Earn (delete_earn.py)

Strengths:

• Excellent use of Counter for aggregating points efficiently
• Clear and intuitive variable naming (take/skip pattern)
• Handles the consecutive number constraint correctly
• More space-efficient than the reference solution for sparse value distributions
• Good use of sorted() to process numbers in order

Areas for Improvement:

• The best_so_far variable is computed in both branches but could be simplified since max(take, skip) is the same in both cases
• Consider adding type hints for better code documentation
• The import statement for List and Counter should be included

VERDICT: PASS