๐ What is Bubble Sort?
Bubble Sort is a simple sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. The pass through the list is repeated until no swaps are needed, which indicates that the list is sorted. It's named 'Bubble Sort' because smaller elements 'bubble' to the top of the list.
๐งฎ What is Selection Sort?
Selection Sort is another simple sorting algorithm that divides the input list into two parts: a sorted sublist and an unsorted sublist. It repeatedly finds the minimum element from the unsorted sublist and moves it to the sorted sublist. The algorithm continues until the entire list is sorted.
๐ Bubble Sort vs. Selection Sort: A Detailed Comparison
| Feature |
Bubble Sort |
Selection Sort |
| Basic Idea |
Repeatedly compares and swaps adjacent elements. |
Repeatedly finds the minimum element and moves it to the sorted part. |
| Swapping |
Swaps adjacent elements frequently. |
Swaps elements fewer times (only when the minimum is found). |
| Time Complexity (Best) |
$O(n)$ (when the list is already sorted) |
$O(n^2)$ |
| Time Complexity (Average) |
$O(n^2)$ |
$O(n^2)$ |
| Time Complexity (Worst) |
$O(n^2)$ |
$O(n^2)$ |
| Space Complexity |
$O(1)$ |
$O(1)$ |
| Stability |
Stable (maintains the relative order of equal elements) |
Unstable (may change the relative order of equal elements) |
| Number of Swaps |
Higher number of swaps. |
Lower number of swaps. |
| Adaptability |
Adaptive (performs better if the input is nearly sorted) |
Not adaptive. |
๐ก Key Takeaways
- โฑ๏ธ Time Complexity: Both have an average and worst-case time complexity of $O(n^2)$, but Bubble Sort can achieve $O(n)$ in the best case.
- ๐ Swapping: Bubble Sort generally involves more swaps than Selection Sort.
- โ๏ธ Stability: Bubble Sort is a stable sorting algorithm, while Selection Sort is typically unstable.
- ๐ฏ Use Cases: Bubble Sort is simple but inefficient for large datasets. Selection Sort performs fewer writes, which can be useful in memory-constrained environments.