pre course classes

[jose-rafael-marcano]

Exercise_1 : Binary Search.

Exercise_2 : Quick sort.

Exercise_3 : Find Mid Point of a Singly Linked List.

Exercise_4 : Merge Sort.

Exercise_5 : Iterative Quick Sort.Exercise_1 : Binary Search.

[super30admin]

1. Exercise_1.java (Binary Search):

   • Correctness: The binary search implementation is mostly correct but has a critical error in initializing high to arr.length instead of r (the parameter passed). This could cause an ArrayIndexOutOfBoundsException.
   • Time Complexity: O(log n) as expected for binary search.
   • Space Complexity: O(1) as expected.
   • Code Quality: The code is clean and readable, with good comments.
   • Efficiency: The overflow prevention in mid calculation is good practice.

2. Exercise_2.java (QuickSort):

   • Correctness: The implementation appears correct with proper partitioning and recursive sorting.
   • Time Complexity: Average case O(n log n), worst case O(n²) as expected.
   • Space Complexity: O(log n) due to recursion stack.
   • Code Quality: Well-structured with clear separation of concerns.
   • Efficiency: The swap method could be optimized to avoid unnecessary swaps when i == j.

3. Exercise_3.java (Linked List Middle):

   • Correctness: Correct implementation using fast and slow pointers.
   • Time Complexity: O(n) as expected.
   • Space Complexity: O(1) as expected.
   • Code Quality: Clean and efficient implementation.
   • Efficiency: Optimal solution for finding the middle.

4. Exercise_4.java (MergeSort):

   • Correctness: Correct implementation of merge sort.
   • Time Complexity: O(n log n) as expected.
   • Space Complexity: O(n) due to temporary arrays.
   • Code Quality: Well-structured with clear method separation.
   • Efficiency: Standard implementation, could consider in-place merge for space optimization.

5. Exercise_5.java (Iterative QuickSort):

   • Correctness: Correct implementation using a stack to avoid recursion.
   • Time Complexity: Average case O(n log n), worst case O(n²) as expected.
   • Space Complexity: O(log n) due to stack usage.
   • Code Quality: Well-structured with good comments.
   • Efficiency: The optimization of pushing larger partitions first is a good touch.

General Strengths:

• Good use of standard algorithms and data structures
• Clean code formatting and structure
• Appropriate comments
• Good handling of edge cases in most implementations

Areas for Improvement:

• Critical bug in binary search implementation
• Could add more edge case testing in main methods
• Some swap operations could be optimized
• Consider adding more comments explaining the algorithms