completed PreCourse-2

[shahan360]

No description provided.

[super30admin]

• Correctness: The base case condition if r >= l is incorrect. It should be if r < l to return -1 when the element is not found. The current implementation returns -1 prematurely.
• Time Complexity: Correctly identified as O(log n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: The code is well-structured and readable. However, the comments are repetitive and could be more concise.
• Efficiency: The implementation is efficient, but the base case logic needs correction.

[super30admin]

Overall, the student has demonstrated a good understanding of the algorithms and data structures required for these exercises. Here's a detailed breakdown for each file:

Exercise_1.py (Binary Search):

• Correctness: The binary search implementation is mostly correct, but there's a logical error in the base case check (if r >= l should return -1 is misplaced). The while loop logic is correct.
• Time Complexity: Correctly identified as O(log n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: Good structure and comments, but the misplaced base case check needs fixing.
• Suggestion: Fix the base case check and ensure proper indentation.

Exercise_2.py (Quick Sort):

• Correctness: The implementation is correct and follows the standard quicksort approach.
• Time Complexity: Correctly identified for average, worst, and best cases.
• Space Complexity: Correctly identified as O(log n) for recursive stack space.
• Code Quality: Well-structured with clear comments in both English and Hindi.
• Suggestion: Consider adding more test cases to verify edge cases.

Exercise_3.py (Linked List Middle):

• Correctness: Correct implementation using the tortoise and hare algorithm.
• Time Complexity: Correctly identified as O(n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: Excellent with detailed comments and explanation of the algorithm.
• Suggestion: The count variable isn't used in the solution - could be removed.

Exercise_4.py (Merge Sort):

• Correctness: Correct implementation of merge sort.
• Time Complexity: Correctly identified as O(n log n).
• Space Complexity: Correctly identified as O(n).
• Code Quality: Good structure with comments in both English and Hindi.
• Suggestion: Consider adding more comments about the merge process.

Exercise_5.py (Iterative Quick Sort):

• Correctness: Correct implementation of iterative quicksort using a stack.
• Time Complexity: Correctly identified for average and worst cases.
• Space Complexity: Correctly identified as O(log n).
• Code Quality: Well-structured with clear comments.
• Suggestion: The stack size could be optimized further.

General Strengths:

1. Good understanding of algorithm complexities
2. Clear comments and explanations
3. Proper use of standard algorithms
4. Good code organization

Areas for Improvement:

1. Some logical errors in base cases (Exercise_1.py)
2. Unused variables (Exercise_3.py)
3. Could benefit from more edge case testing
4. Some redundant comments could be removed for brevity