PreCourse-2 Completed

[anushrihub]

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[super30admin]

Let's evaluate each exercise one by one:

Exercise_1.py (Binary Search):

• Correctness: The solution correctly implements binary search but has an unnecessary sort at the beginning which changes the original array's indices. This is incorrect as binary search requires the input array to already be sorted.
• Time Complexity: O(log n) for the search, but O(n log n) overall due to the sort.
• Space Complexity: O(1) as claimed.
• Code Quality: The code is readable but the sorting step should be removed.
• Efficiency: Remove the sorting step to maintain O(log n) time complexity.

Exercise_2.py (QuickSort):

• Correctness: The implementation is mostly correct but has a bug in the partition function where the swap happens inside the while loop but should happen after it.
• Time Complexity: O(n log n) as claimed.
• Space Complexity: O(log n) due to recursion stack, not O(1) as claimed.
• Code Quality: Good structure and comments, but needs to fix the partition logic.
• Efficiency: The partition logic needs to be corrected for proper sorting.

Exercise_3.py (Linked List Middle):

• Correctness: Correctly finds the middle element but returns the element after the middle for even-length lists (should return the first middle element).
• Time Complexity: O(n) as claimed.
• Space Complexity: O(1) as claimed.
• Code Quality: Well-structured and readable.
• Efficiency: Could be optimized to find the middle in one pass using slow/fast pointers.

Exercise_4.py (MergeSort):

• Correctness: Correct implementation of merge sort.
• Time Complexity: O(n log n) as claimed.
• Space Complexity: O(n) as claimed.
• Code Quality: Good structure and comments.
• Efficiency: The implementation is efficient and follows standard merge sort approach.

Exercise_5.py (Iterative QuickSort):

• Correctness: Similar partition bug as Exercise_2. Also, the partition function returns inside the while loop which is incorrect.
• Time Complexity: O(n log n) as claimed.
• Space Complexity: O(log n) as claimed (due to stack usage).
• Code Quality: Good structure but needs to fix the partition logic.
• Efficiency: The partition logic needs to be corrected for proper sorting.

General feedback:

1. The student demonstrates good understanding of algorithms but needs to pay attention to edge cases.
2. Some implementations have bugs in partition logic that need fixing.
3. Time and space complexity analysis is mostly correct but needs to be more precise in some cases.
4. Code quality is generally good with proper comments and structure.
5. The binary search implementation incorrectly sorts the input array.