Completed PreCourse-2

[PritPanchani]

No description provided.

[super30admin]

Note: If the solution is correct and follows best practices, the verdict should be PASS. If there are minor issues that don't affect correctness but could be improved, the verdict should still be PASS. Only use NEEDS_IMPROVEMENT if there are significant errors or issues that would prevent the solution from working correctly in some cases.

Now, please evaluate the student's solution.

[super30admin]

Let's evaluate each exercise one by one:

Exercise_1 (Binary Search):

• Correctness: The binary search implementation is correct. It uses a while loop to narrow down the search range by comparing the middle element with the target.
• Time Complexity: O(log n), which is optimal for binary search.
• Space Complexity: O(1), as it uses only a constant amount of extra space.
• Code Quality: The code is clean and readable. The variable names are appropriate, and the logic is straightforward.
• Potential Issues: None. This is a standard iterative binary search.

Exercise_2 (QuickSort):

• Correctness: The partition function uses the last element as the pivot and correctly partitions the array. The recursive sort function is implemented correctly.
• Time Complexity: Average case O(n log n), worst case O(n^2) if the pivot is poorly chosen (e.g., already sorted array with last element as pivot).
• Space Complexity: O(log n) for the recursive call stack in the average case, but O(n) in the worst case.
• Code Quality: The code is well-structured. The swap method is defined separately, which is good. However, the pivot selection strategy (last element) may lead to worst-case performance on already sorted arrays. Consider using a randomized pivot or median-of-three for better performance.
• Potential Issues: The worst-case time complexity might be a concern for large sorted arrays.

Exercise_3 (Linked List - Find Middle):

• Correctness: The current implementation has a bug. The while loop condition while(slow != null && fast != null) is incorrect because when fast becomes null, fast.next would cause a NullPointerException. Also, the loop should continue until fast reaches the end. Moreover, when the list has even number of nodes, there are two middle nodes; typically we return the first one or the second one based on requirement? The problem says "print middle", so it should print one of them. But the code might crash.
• Time Complexity: O(n), which is correct.
• Space Complexity: O(1), correct.
• Code Quality: The code structure is good, but the logic is flawed. The condition should be while (fast != null && fast.next != null) to avoid NullPointerException. Also, after the loop, slow points to the middle. But in the current code, it prints after the loop without checking if slow is null.
• Improvement: Change the loop condition to while (fast != null && fast.next != null), and then print slow.data. Also, handle the case when the list is empty (already done).

Exercise_4 (MergeSort):

• Correctness: There is a bug in the merge function. When copying the right subarray, it uses L[j] = arr[m+1+j]; which should be R[j] = arr[m+1+j];. This will cause incorrect merging because the right array is being copied into the left array.
• Time Complexity: O(n log n), correct.
• Space Complexity: O(n) for the temporary arrays, which is standard for merge sort.
• Code Quality: The code is mostly well-structured, but the bug indicates a lack of testing. The variable names are clear, but the error is critical.
• Improvement: Fix the copy for the right subarray: change L[j] to R[j] in the second loop.

Exercise_5 (Iterative QuickSort):

• Correctness: The partition function is similar to Exercise_2 and correct. The iterative approach using a stack is implemented correctly. However, the swap method uses arithmetic operations which might cause integer overflow if the numbers are large. Also, it doesn't work correctly when i and j are the same (but the condition if (i != j) prevents that).
• Time Complexity: Average case O(n log n), worst case O(n^2) due to pivot selection.
• Space Complexity: O(log n) for the stack in the average case, but O(n) in the worst case.
• Code Quality: The iterative approach is well implemented. However, the swap method could be improved to use a temporary variable to avoid potential overflow. Also, the pivot selection is the last element, which might lead to worst-case behavior.
• Improvement: Consider changing the swap method to use a temporary variable. Also, consider using a better pivot selection (e.g., median-of-three) to avoid worst-case scenarios.

Overall, the student demonstrates a good understanding of the algorithms but has some critical bugs in Exercise_3 and Exercise_4. The code quality is generally good, but attention to detail is needed.