Sorting algorithms are essential tools in computer science and programming. They help organize data efficiently, making it easier to search and manipulate. In this guide, we will explore some of the most common sorting algorithms and their implementations.
Common Sorting Algorithms
1. 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 the list is sorted.
- Time Complexity: O(n^2)
- Space Complexity: O(1)
2. Selection Sort
Selection sort is an in-place comparison sort. It divides the input list into two parts: a sorted sublist of items which is built up from left to right at the front (left) of the list, and a sublist of the remaining unsorted items that occupy the rest of the list.
- Time Complexity: O(n^2)
- Space Complexity: O(1)
3. Insertion Sort
Insertion sort is a simple sorting algorithm that builds the final sorted array one item at a time. It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort.
- Time Complexity: O(n^2)
- Space Complexity: O(1)
4. Merge Sort
Merge sort is a divide and conquer algorithm that divides the input array into two halves, calls itself for the two halves, and then merges the two sorted halves. The merge function is used for merging two halves.
- Time Complexity: O(n log n)
- Space Complexity: O(n)
5. Quick Sort
Quick sort is a highly efficient sorting algorithm and is based on partitioning of array of data into smaller arrays. A large array is partitioned into two arrays one of which holds values smaller than the specified value, say pivot, based on which the partition is made and another array holds values greater than the pivot value.
- Time Complexity: O(n log n)
- Space Complexity: O(log n)
Learning Resources
For further reading on sorting algorithms, we recommend checking out our comprehensive guide on Sorting Algorithms.