PreCourse-2 Completed

[pranavs0133]

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[super30admin]

Exercise_1.java (Binary Search):

• Correctness: The implementation correctly follows the binary search algorithm, returning the index of the target element if found, otherwise -1.
• Time Complexity: O(log n) as correctly stated, since the search space is halved in each iteration.
• Space Complexity: O(1) as correctly stated, since no additional space is used beyond a few variables.
• Code Quality: The code is clean and well-structured. The use of while(l <= r) ensures all elements are checked.
• Efficiency: No optimizations needed; this is a standard and efficient implementation.

Exercise_2.java (QuickSort):

• Correctness: The implementation correctly follows the QuickSort algorithm, including the partition step and recursive sorting.
• Time Complexity: O(n^2) in the worst case (as correctly noted), but average case is O(n log n).
• Space Complexity: O(1) for the iterative operations, but O(log n) for the recursive call stack (not mentioned in the comments).
• Code Quality: The code is well-structured. The partition logic is clear, and the recursive calls are correctly implemented.
• Efficiency: The base case if(high <= low) could be optimized to if(low < high) to avoid unnecessary calls when low == high.

Exercise_3.java (Linked List Middle Element):

• Correctness: The implementation correctly finds the middle element using the fast and slow pointer technique.
• Time Complexity: O(n) as correctly stated, since the fast pointer traverses the list once.
• Space Complexity: O(1) as correctly stated, since only two pointers are used.
• Code Quality: The code is clean and easy to understand. The use of fast != null && fast.next != null ensures correctness for both even and odd-length lists.
• Efficiency: No optimizations needed; this is the optimal approach.

Exercise_4.java (MergeSort):

• Correctness: The implementation correctly follows the MergeSort algorithm, including the merge step.
• Time Complexity: O(n log n) as correctly stated, due to the divide-and-conquer approach.
• Space Complexity: O(n) as correctly stated, due to the temporary arrays used during merging.
• Code Quality: The code is well-structured, though the merge logic could be slightly more concise. The use of lArr and rArr is clear.
• Efficiency: The merge step is efficient, but the temporary arrays could be reused to minimize memory allocations.

Exercise_5.java (Iterative QuickSort):

• Correctness: The implementation correctly follows the QuickSort algorithm iteratively using a stack.
• Time Complexity: O(n^2) in the worst case (as correctly noted), but average case is O(n log n).
• Space Complexity: O(n) for the stack, as correctly stated.
• Code Quality: The code is well-structured, but the swap method could be simplified to use a temporary variable for clarity and to avoid potential issues with overflow.
• Efficiency: The iterative approach avoids recursion stack overhead, but the swap method could be optimized for readability and safety.

General Feedback:

• The student demonstrates a strong understanding of algorithms and data structures.
• Time and space complexity analysis is generally accurate and well-documented.
• Code quality is high, with clear and readable implementations.
• Minor improvements could be made in some areas, such as optimizing base cases and simplifying swap operations.