Optimized Recursive Knapsack with Memoization #12550
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- Added memoization to avoid redundant calculations - Improved function readability with better parameter naming - Ensured correct handling of empty inputs - Reduced time complexity from O(2ⁿ) to O(n * max_weight)
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
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hey freinds review it please for adding it in github repository |
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Summary
This PR improves the recursive implementation of the Knapsack Problem by adding memoization, reducing the time complexity from O(2ⁿ) to O(n × max_weight).
Changes Made:
✅ Added Memoization using a dictionary to store previously computed results.
✅ Optimized Recursion by avoiding redundant calculations.
✅ Improved Function Readability with clear parameter names and better docstrings.
✅ Maintained the Same Functionality but with better efficiency.
✅ Retained Doctests to ensure correctness.
Performance Improvement:
The previous approach was exponential O(2ⁿ) and inefficient for large inputs.
The new approach is O(n × max_weight), making it significantly faster.
Test Cases:
The function has been tested with sample cases:
Additional Notes:
Looking forward to feedback! 🚀