Completed Precourse 2

[Shalinid8]

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[super30admin]

1. Correctness:

   • Exercise_1.py: The binary search implementation is correct and follows the standard recursive approach.
   • Exercise_2.py: The quicksort implementation is correct, including the partition function.
   • Exercise_3.py: The middle element detection in a linked list is correctly implemented using the slow-fast pointer technique.
   • Exercise_4.py: The merge sort implementation has a logical error in the recursive calls and array slicing, which would cause incorrect sorting.
   • Exercise_5.py: The iterative quicksort implementation is correct and efficiently uses a stack to simulate recursion.

2. Time Complexity:

   • The student has correctly identified the time complexity for each exercise:
     • Binary Search: O(log n)
     • Quicksort: O(n log n)
     • Middle of Linked List: O(n)
     • Merge Sort: O(n log n)
     • Iterative Quicksort: O(n log n)

3. Space Complexity:

   • The space complexity analysis is mostly correct, except for Exercise_4.py (Merge Sort), where the student incorrectly states O(n) due to temp arrays. The implementation actually creates new arrays in each recursive call, leading to higher space usage.

4. Code Quality:

   • The code is generally well-structured and readable.
   • Comments are clear and helpful.
   • Variable names are appropriate.
   • The merge sort implementation (Exercise_4.py) needs improvement in handling array indices and avoiding unnecessary array slicing.

5. Efficiency:

   • Exercise_4.py could be optimized by avoiding array slicing and using indices to represent subarrays.
   • The iterative quicksort (Exercise_5.py) is efficient and avoids recursion stack overhead.