C - Sorting algorithms & Big O

• A project during my Full Stack Software Engineering studies at ALX Africa, a course offered by Holberton School.

Technologies

• Files written in vi, vim, and emacs editors.
• C files compiled using gcc 9.4.0.
• C files wriiten according to the betty coding style. Checked using betty-style.pl and betty-doc.pl.
• Files tested on Ubuntu 20.04 LTS using gcc.

Files

Filename	Description
0-bubble_sort.c	Write a function that sorts an array of integers in ascending order using the Bubble sort algorithm
1-insertion_sort_list.c	Write a function that sorts a doubly linked list of integers in ascending order using the Insertion sort algorithm.
2-selection_sort.c	Write a function that sorts an array of integers in ascending order using the Selection sort algorithm.
3-quick_sort.c	Write a function that sorts an array of integers in ascending order using the Quick sort algorithm.
100-shell_sort.c	Write a function that sorts an array of integers in ascending order using the Shell sort algorithm, using the Knuth sequence
101-cocktail_sort_list.c	Write a function that sorts a doubly linked list of integers in ascending order using the Cocktail shaker sort algorithm.
102-counting_sort.c	Write a function that sorts an array of integers in ascending order using the Counting sort algorithm.
103-merge_sort.c	Write a function that sorts an array of integers in ascending order using the Merge sort algorithm.
104-heap_sort.c	Write a function that sorts an array of integers in ascending order using the Heap sort algorithm.
105-radix_sort.c	Write a function that sorts an array of integers in ascending order using the Radix sort algorithm
106-bitonic_sort.c	Write a function that sorts an array of integers in ascending order using the Bitonic sort algorithm

Other Files

* -O Files : The big O notations of the time complexity of the each algorithm, with 1 notation per line:

• 1. in the best case
• 2. in the average case
• 3. in the worst case

The formats:

• O(1)
• O(n)
• O(n!)
• n square -> O(n^2)
• log(n) -> O(log(n))
• n * log(n) -> O(nlog(n))
• n + k -> O(n+k)
• …