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Computer Science — Sorting Algorithms

Common sorting algorithms, time complexities, and approaches

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algorithmia_x 15 terms Feb 14, 2026
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Terms 15

1
Bubble Sort
Repeatedly swaps adjacent elements if in wrong order; O(n²) average
2
Selection Sort
Finds minimum and moves to front each pass; O(n²)
3
Insertion Sort
Builds sorted array one element at a time; efficient for small arrays; O(n²)
4
Merge Sort
Divide and conquer; splits and merges; O(n log n) guaranteed
5
Quick Sort
Picks pivot and partitions around it; O(n log n) average, O(n²) worst
6
Heap Sort
Builds max heap then extracts elements; O(n log n) in-place
7
Radix Sort
Non-comparison sort by digit; O(nk) where k is number of digits
8
Counting Sort
Counts occurrences of each value; O(n+k); only for integers
9
Stable Sort
Preserves relative order of equal elements; e.g. Merge Sort
10
In-place Sort
Sorts without significant extra memory; e.g. Quick Sort, Heap Sort
11
Time Complexity
How runtime grows relative to input size; expressed in Big O notation
12
Space Complexity
Memory usage relative to input size
13
Divide and Conquer
Algorithm strategy breaking problem into smaller subproblems recursively
14
Best Case
Minimum operations needed; often O(n) for nearly sorted input
15
Worst Case
Maximum operations in the least favorable input scenario