Pre-Course 2

[KartavyaBhatt]

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[super30admin]

Let me analyze each exercise:

Exercise 1: Binary Search

• Correctness: The iterative binary search implementation is correct. It properly handles the search by narrowing down the search space.
• Time Complexity: O(logn) - correct
• Space Complexity: O(1) - correct
• Code Quality: Good with clear comments explaining the approach. The logic is sound.
• Edge Cases: Missing boundary checks for empty arrays (though l <= r would handle it if l > r initially). The code handles element not found correctly.

Exercise 2: Quick Sort (Recursive)

• Correctness: The partition function correctly places the pivot in its final position. The recursive quicksort properly sorts the array.
• Time Complexity: O(nlogn) average, O(n²) worst - correct
• Space Complexity: O(logn) average, O(n) worst - correct
• Learning Resources: Good that they documented resources used.
• Minor Issue: The partition logic could be slightly more efficient by using a while loop instead of for loop with manual wall management, but current approach is correct.

Exercise 3: Find Middle of Linked List

• Correctness: The two-pointer approach is correct for finding the middle element. The logic handles both odd and even length lists.
• Time Complexity: O(n) - correct
• Space Complexity: O(1) - correct
• Code Quality: Good comments explaining the approach. The implementation is clean.
• Edge Cases: The initial check if p1 is None or p2 is None handles empty list and single element list correctly.

Exercise 4: Merge Sort

• Correctment: The merge sort implementation is correct. It divides the array, sorts recursively, and merges properly.
• Time Complexity: O(nlogn) - correct
• Space Complexity: O(n) - correct
• Space Optimization Note: The student mentions wanting to do in-place merge but chose to use extra space. This is a valid approach.
• Bug: There's a subtle bug in the recursive call condition. The condition if m+1 < h should be if m+1 <= h to handle the case when m+1 == h (last element). This could cause some elements to not be sorted in certain edge cases.

Exercise 5: Quick Sort (Iterative)

• Correctness: The iterative quicksort using a stack to simulate recursion is a good approach. The partition function is reused from Exercise 2.
• Time Complexity: O(nlogn) average, O(n²) worst - correct
• Space Complexity: O(n) for the stack - correct
• Code Quality: Clean implementation using a list as a stack. Good use of explicit stack management.

Overall Assessment:
The student demonstrates a good understanding of fundamental sorting algorithms and data structures. The code is well-documented with comments explaining the approach. There's a minor bug in Exercise 4's merge sort condition that should be fixed. The student shows good self-awareness about areas where they need more practice (noted in comments).