Create ShellSortAditya.java#653
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Shell Sort is an optimized version of Insertion Sort that allows the exchange of far-apart elements. The array is sorted using gaps that reduce by half each iteration. When the gap becomes 1, it effectively becomes a normal insertion sort — but the array is mostly sorted by then. Complexity: Best case: O(n log n) Average case: O(n^(3/2)) Worst case: O(n²) Space complexity: O(1)
💎 Code Quality Check Results❌ Missing Complexity AnalysisThese files don't include time/space complexity:
Required: Add comments explaining time and space complexity (e.g., ❌ Missing Algorithm DescriptionThese files don't explain what the algorithm does:
Required: Add a description explaining the algorithm, its purpose, and how it works 📚 Quality StandardsTo maintain high quality, every contribution should include:
💡 Example Template"""
Binary Search Algorithm
Description: Searches for a target value in a sorted array using divide-and-conquer
Time Complexity: O(log n) - halves search space each iteration
Space Complexity: O(1) - only uses constant extra space
"""
def binary_search(arr, target):
# Initialize pointers
left, right = 0, len(arr) - 1
while left <= right:
mid = (left + right) // 2
# Check if target found
if arr[mid] == target:
return mid
# Search right half
elif arr[mid] < target:
left = mid + 1
# Search left half
else:
right = mid - 1
return -1 # Not found
# Test cases
if __name__ == "__main__":
test_arr = [1, 3, 5, 7, 9]
print(binary_search(test_arr, 5)) # Output: 2
print(binary_search(test_arr, 6)) # Output: -1🔧 How to Fix
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🤖 Automated PR Status🔍 Code Validation✅ Passed - File naming and structure look good! 🧪 Compilation Tests❌ Failed - Please fix compilation errors and try again. 📋 Overall Status
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Shell Sort is an optimized version of Insertion Sort that allows the exchange of far-apart elements.
The array is sorted using gaps that reduce by half each iteration.
When the gap becomes 1, it effectively becomes a normal insertion sort — but the array is mostly sorted by then.
Complexity:
Best case: O(n log n)
Average case: O(n^(3/2))
Worst case: O(n²)
Space complexity: O(1)