python coding test course, bubble sort

Hello! In this blog post, we will discuss Bubble Sort, an algorithm problem-solving course for job preparation. We will understand the concept of the bubble sort algorithm and examine how to implement it during the coding test preparation process. Through this article, I hope to deepen your understanding of bubble sort’s operation, as well as compare it with other sorting algorithms based on this knowledge.

What is Bubble Sort?

Bubble Sort is one of the sorting algorithms, the simplest method of sorting data. This algorithm compares two adjacent elements and swaps their positions if they are in the wrong order. This process is repeated until the entire array is sorted. The name ‘bubble’ comes from the way the largest elements ‘float’ to the end of the array.

The Working Principle of Bubble Sort

The basic process of bubble sort is as follows:

  1. Compare the first and second elements, and swap their positions if they are not in the correct order.
  2. Compare the second and third elements, and swap their positions if they are not in the correct order.
  3. Proceed in this manner until the end of the array. This single pass is called a pass.
  4. Repeat this process until all elements of the array have been checked.

Once sorting is completed, the entire array is sorted in ascending order. Let’s look at this process with an example.

Example

Given a number array:

[5, 1, 4, 2, 8]

We will examine the process of sorting this array using the bubble sort algorithm.

Step 1: First Pass

  • [5, 1, 4, 2, 8] → Compare 5 and 1 (5 > 1) → [1, 5, 4, 2, 8]
  • [1, 5, 4, 2, 8] → Compare 5 and 4 (5 > 4) → [1, 4, 5, 2, 8]
  • [1, 4, 5, 2, 8] → Compare 5 and 2 (5 > 2) → [1, 4, 2, 5, 8]
  • [1, 4, 2, 5, 8] → Compare 5 and 8 (5 < 8) → [1, 4, 2, 5, 8]

Step 2: Second Pass

  • [1, 4, 2, 5, 8] → Compare 1 and 4 (1 < 4) → [1, 4, 2, 5, 8]
  • [1, 4, 2, 5, 8] → Compare 4 and 2 (4 > 2) → [1, 2, 4, 5, 8]
  • [1, 2, 4, 5, 8] → Compare 4 and 5 (4 < 5) → [1, 2, 4, 5, 8]
  • [1, 2, 4, 5, 8] → Compare 5 and 8 (5 < 8) → [1, 2, 4, 5, 8]

Step 3: Third Pass

  • [1, 2, 4, 5, 8] → Compare 1 and 2 (1 < 2) → [1, 2, 4, 5, 8]
  • [1, 2, 4, 5, 8] → Compare 2 and 4 (2 < 4) → [1, 2, 4, 5, 8]
  • [1, 2, 4, 5, 8] → Compare 4 and 5 (4 < 5) → [1, 2, 4, 5, 8]
  • [1, 2, 4, 5, 8] → Compare 5 and 8 (5 < 8) → [1, 2, 4, 5, 8]

We continue this process until sorting is complete. As a result, the above array is sorted to [1, 2, 4, 5, 8].

Implementing the Bubble Sort Algorithm

Now, let’s implement the bubble sort algorithm using Python. Below is a simple bubble sort program:


def bubble_sort(arr):
    n = len(arr)
    for i in range(n):
        # The last n-i elements are already sorted
        for j in range(0, n-i-1):
            # Compare two adjacent elements
            if arr[j] > arr[j+1]:
                arr[j], arr[j+1] = arr[j+1], arr[j]  # Swap positions
    return arr

# Example array
numbers = [5, 1, 4, 2, 8]
sorted_numbers = bubble_sort(numbers)
print(sorted_numbers)  # Output: [1, 2, 4, 5, 8]

Time Complexity of Bubble Sort

The time complexity of bubble sort is O(n²) in the worst case. This occurs because it compares all elements. However, if an already sorted array is given, it can operate normally and may have a best-case time complexity of O(n). This is when no swaps occur during each pass.

Advantages and Disadvantages of Bubble Sort

Advantages of Bubble Sort:

  • It is simple to implement and easy to understand.
  • The sorted state of the array can be easily observed.

Disadvantages of Bubble Sort:

  • The time complexity is O(n²), making it inefficient.
  • It performs poorly compared to other sorting algorithms for large datasets.

Comparison of Bubble Sort with Other Sorting Algorithms

There are various sorting algorithms, including selection sort, insertion sort, merge sort, and quick sort, in addition to bubble sort. The characteristics of each algorithm are as follows:

  1. Selection Sort: Finds the minimum (or maximum) value in the array during each iteration to sort it. Its time complexity is O(n²).
  2. Insertion Sort: Sorts by placing each element in its appropriate position. It has a worst-case of O(n²) and a best-case of O(n).
  3. Merge Sort: Uses a divide-and-conquer approach to sort data. Its time complexity is O(n log n).
  4. Quick Sort: Sorts by partitioning the array around a pivot. On average, its time complexity is O(n log n).

Tips for Studying Algorithms

Implementing and understanding basic algorithms like bubble sort is very important. I recommend the following approaches for solving algorithm problems:

  • When implementing an algorithm, try writing it out by hand first, then code it.
  • Create various test cases to try out.
  • Share your code with others for feedback.
  • Gradually increase the difficulty by solving similar problems.

Conclusion

In this post, we provided insights into the basic concepts and implementation methods of the bubble sort algorithm, as well as comparing it with other algorithms. To improve algorithm problem-solving skills, much practice is needed, and trying various problems is essential. In the next post, we will explore other sorting algorithms and discuss their differences.

Q&A

If you have any questions about this blog post, please leave a comment. I hope this helps!