This application shows a way to visualize different sorting algorithms.
It is written in native JavaScript, no additional libraries were used.
I wanted to make this project after seeing many videos online about visualizing different sorting algorithms and I wanted to make my own version.
"In-place" algorithms like Bubble and Insertion Sort were quite trivial to implemement.
However, "Divide and Conquer" algorithms such as Merge Sort, where we have to keep track of sub-arrays were more difficult as keeping the position of the elements in the overall array was complicated.
| Algorithm | Time Complexity | Space Complexity | ||||
|---|---|---|---|---|---|---|
| Best Case | Average Case | Worst Case | Worst Case | |||
| Bubble Sort | Ω(n) |
Θ(n²) |
O(n²) |
O(1) |
||
| Insertion Sort | Ω(n) |
Θ(n²) |
O(n²) |
O(1) |
||
| Selection Sort | Ω(n²) |
Θ(n²) |
O(n²) |
O(1) |
||
| Cocktail Sort | Ω(n²) |
Θ(n²) |
O(n²) |
O(1) |
||
| Pancake Sort | Ω(n²) |
Θ(n²) |
O(n²) |
O(1) |
||
| Shell Sort | Ω(n log(n)) |
Θ(n log²(n)) |
O(n log²(n)) |
O(1) |
||
| Quick Sort | Ω(n log(n)) |
Θ(n log(n)) |
O(n²) |
O(Log(n)) |
||
| Merge Sort | Ω(n log(n)) |
Θ(n log(n)) |
O(n log(n)) |
O(N) |
||
| Heap Sort | Ω(n log(n)) |
Θ(n log(n)) |
O(n log(n)) |
O(1) |
||
| Bucket Sort | Ω(n+k) |
Θ(n+k) |
O(n²) |
O(n) |
||
| Radix Sort | Ω(nk) |
Θ(nk) |
O(nk) |
O(n+k) |
It is not required to download this repository to run the application.
Opening this link will bring you to a HTML preview through Github to run it.
However, if you want to use it offline, download as a zip or clone the repository. You can then open index.html to play.