Completed Precourse 2

[Srijha09]

No description provided.

[super30admin]

The student's solution demonstrates a good understanding of fundamental algorithms and data structures. Here's a detailed evaluation for each exercise:

Exercise_1.py (Binary Search):

• Correctness: The implementation correctly follows the binary search algorithm.
• Time Complexity: Correctly identified as O(log n).
• Space Complexity: Correctly identified as O(1).
• Code Quality: Well-structured and readable. The docstring could be more detailed.
• Improvement: The parameters 'l' and 'r' in the function signature are redundant since they're immediately overwritten.

Exercise_2.py (QuickSort):

• Correctness: The implementation correctly follows the QuickSort algorithm with proper partitioning.
• Time Complexity: Correctly identified as O(n log n) average and O(n^2) worst case.
• Space Complexity: Correctly identified as O(log n) due to recursion stack.
• Code Quality: Good structure and readability. The docstring for partition is excellent.
• Improvement: Could add more comments explaining the recursive process in quickSort.

Exercise_3.py (Linked List Middle Element):

• Correctness: Correctly implements the slow/fast pointer approach.
• Time Complexity: O(n) (though not explicitly mentioned).
• Space Complexity: O(1) (though not explicitly mentioned).
• Code Quality: Good structure. The printMiddle method could have a more detailed docstring.
• Improvement: Could handle edge cases like single-node lists more explicitly.

Exercise_4.py (MergeSort):

• Correctness: Correct implementation of MergeSort.
• Time Complexity: Correctly identified as O(n log n).
• Space Complexity: Correctly identified as O(n).
• Code Quality: Well-structured. Could benefit from more detailed docstrings.
• Improvement: The merge process could be extracted to a separate function for better modularity.

Exercise_5.py (Iterative QuickSort):

• Correctness: Correct implementation of iterative QuickSort using a stack.
• Time Complexity: Correctly identified as O(n log n) average and O(n^2) worst case.
• Space Complexity: Correctly identified as O(log n) to O(n).
• Code Quality: Good structure. The docstring could mention the iterative nature.
• Improvement: Could add comments explaining the stack operations.

General Strengths:

• Consistent style and formatting
• Correct time/space complexity analysis
• Proper use of docstrings
• Good handling of edge cases

Areas for Improvement:

• More detailed docstrings explaining algorithms
• Consistent handling of edge cases across all exercises
• Some redundant parameters could be removed
• Could add more test cases