Repeat this process until the last element remains sorted.<\/li>\n<\/ol>\n2. Problem Definition<\/h2>\n
Given an integer array, sort this array in ascending order using Bubble Sort.<\/p>\n
\nInput: [64, 34, 25, 12, 22, 11, 90]\nOutput: [11, 12, 22, 25, 34, 64, 90]\n<\/pre>\n3. Implementation of Swift Code<\/h2>\n
Now, let\u2019s write the code to solve this problem using Swift.<\/p>\n
\nfunc bubbleSort(arr: [Int]) -> [Int] {\n var sortedArray = arr\n let n = sortedArray.count\n \n for i in 0.. sortedArray[j+1] {\n \/\/ Swap\n let temp = sortedArray[j]\n sortedArray[j] = sortedArray[j+1]\n sortedArray[j+1] = temp\n }\n }\n }\n return sortedArray\n}\n\n\/\/ Example execution\nlet array = [64, 34, 25, 12, 22, 11, 90]\nlet sortedArray = bubbleSort(arr: array)\nprint(sortedArray) \/\/ Output: [11, 12, 22, 25, 34, 64, 90]\n<\/pre>\n4. Code Execution Example<\/h2>\n
When we execute the above Swift code, the given array is successfully sorted. In this code, we use two nested for loops to compare all the elements of the array. This can be time-consuming, but the true advantage of Bubble Sort is its intuitive nature.<\/p>\n
5. Optimization and Improvement Methods<\/h2>\n
Bubble Sort has a time complexity of O(n^2), which is inefficient. However, a few simple optimization techniques can be applied:<\/p>\n
\n- Early termination:<\/strong> If no swaps occur during a pass, the array is already sorted, so no further comparisons are necessary.<\/li>\n
- Reducing the range of comparisons:<\/strong> Elements at both ends that have already been passed don\u2019t need to be compared in subsequent passes.<\/li>\n<\/ul>\n
The code with these optimizations can be modified as follows:<\/p>\n
\nfunc optimizedBubbleSort(arr: [Int]) -> [Int] {\n var sortedArray = arr\n let n = sortedArray.count\n var swapped: Bool\n \n for i in 0.. sortedArray[j+1] {\n \/\/ Swap\n let temp = sortedArray[j]\n sortedArray[j] = sortedArray[j+1]\n sortedArray[j+1] = temp\n swapped = true\n }\n }\n \/\/ If no swaps occurred, sorting is complete, so exit\n if !swapped {\n break\n }\n }\n return sortedArray\n}\n<\/pre>\n6. Time Complexity of Bubble Sort<\/h2>\n
The time complexity of Bubble Sort is O(n^2) in both average and worst-case scenarios. The best case (when the array is already sorted) can be O(n), making it more efficient. For this reason, Bubble Sort may be effective on small data sets, but in real applications, it is common to use more efficient sorting algorithms.<\/p>\n
Conclusion<\/h2>\n
In this course, we had the opportunity to implement Bubble Sort using Swift and learn the basics of algorithm sorting. By solving basic problems like sorting an array, we were able to understand the workings and time complexity of algorithms. In the next course, we will cover a more efficient sorting algorithm called Quick Sort. Thank you for being with us!<\/p>\n
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