What is Bubble Sort?
Bubble Sort is a straightforward comparison-based sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. This process continues until the list is sorted.
How Bubble Sort Works
To understand Bubble Sort, let’s break it down step-by-step using an example.
Example Array: [64, 34, 25, 12, 22, 11, 90]
Initial State: [64, 34, 25, 12, 22, 11, 90]
First Pass:
Compare 64 and 34: Swap them. [34, 64, 25, 12, 22, 11, 90]
Compare 64 and 25: Swap them. [34, 25, 64, 12, 22, 11, 90]
Compare 64 and 12: Swap them. [34, 25, 12, 64, 22, 11, 90]
Compare 64 and 22: Swap them. [34, 25, 12, 22, 64, 11, 90]
Compare 64 and 11: Swap them. [34, 25, 12, 22, 11, 64, 90]
At the end of the first pass, the largest element (90) is in its correct position.
Second Pass:
Repeat the comparisons and swaps as above but ignore the last element (90) which is already sorted.
Subsequent Passes:
Continue the process, reducing the number of elements to check each time until no swaps are needed, indicating that the list is sorted.
Final Sorted Array: [11, 12, 22, 25, 34, 64, 90]
Key Characteristics of Bubble Sort
Time Complexity:
Best Case: O(n) – When the list is already sorted, Bubble Sort performs a single pass with no swaps.
Average Case: O(n²) – The average number of comparisons and swaps is quadratic in nature.
Worst Case: O(n²) – Occurs when the list is sorted in reverse order, requiring the maximum number of comparisons and swaps.
Space Complexity: O(1) – Bubble Sort is an in-place sorting algorithm, meaning it requires only a constant amount of additional space.
Stability: Bubble Sort is a stable sort, meaning that it preserves the relative order of equal elements.
Advantages and Disadvantages
Advantages:
Simplicity: Easy to understand and implement, making it a good educational tool.
No Additional Space Required: Operates in-place, making it space-efficient.
Disadvantages:
Inefficiency: Highly inefficient for large datasets due to its quadratic time complexity.
Performance: Generally slower compared to more advanced sorting algorithms like Quick Sort or Merge Sort.
When to Use Bubble Sort
Educational Purposes: Ideal for teaching the basics of sorting and algorithm design.
Small Datasets: Can be used for small lists where its inefficiency is not a concern.
Nearly Sorted Data: Performs well if the list is nearly sorted, with fewer passes needed.
Conclusion
Bubble Sort, while not suitable for large-scale applications due to its inefficiency, is a foundational algorithm in computer science. Its simplicity and ease of understanding make it a valuable tool for learning sorting principles.
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