Pre Course 2 Complete

[PrasiddhShah]

No description provided.

[super30admin]

Overall, the student has demonstrated a good understanding of fundamental algorithms and data structures. Here's a detailed evaluation of each exercise:

Exercise 1 (Binary Search):

• Correctness: The binary search implementation is correct and uses an iterative approach.
• Time Complexity: Correctly identified as O(log n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: Well-structured and readable. Good use of comments.
• Improvement: Could add input validation for null arrays.

Exercise 2 (QuickSort):

• Correctness: Implementation appears correct using Hoare's partition scheme.
• Time Complexity: Correctly identified as O(n log n) average case.
• Space Complexity: Correctly identified as O(log n) for recursion stack.
• Code Quality: Good structure but could benefit from more comments explaining the partition logic.
• Improvement: The student mentioned uncertainty about the logic - suggesting they review the partitioning algorithm more thoroughly.

Exercise 3 (Linked List Middle):

• Correctness: Correct implementation using fast/slow pointer technique.
• Time Complexity: Correctly identified as O(n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: Clean and well-structured. Good use of inner Node class.
• Improvement: Could handle edge case of empty list.

Exercise 4 (MergeSort):

• Correctness: Implementation appears correct.
• Time Complexity: Correctly identified as O(n log n).
• Space Complexity: Correctly identified as O(n).
• Code Quality: Good structure but using ArrayList adds some overhead.
• Improvement: Could be optimized by using primitive arrays instead of ArrayList.

Exercise 5 (Iterative QuickSort):

• Correctness: Implementation appears correct.
• Time Complexity: Correctly identified as O(n log n).
• Space Complexity: Correctly identified as O(log n).
• Code Quality: Similar to recursive version, could use more comments.
• Improvement: Student expressed uncertainty - suggesting they review the iterative approach more.

General Observations:

1. Strengths:

• Good understanding of time/space complexity
• Mostly correct implementations
• Proper use of standard algorithms
• Good code organization

2. Areas for Improvement:

• More thorough testing of edge cases
• Some implementations could be more memory efficient
• More detailed comments in complex sections
• Greater confidence in implementations (particularly QuickSort variants)