Running Deeper C++/C/Java

Radix sort uses a length based type of comparison, and has a time complexity of O(wn), where w is the length of the data. For cases where w is constant, and n is very large, the complexity O(wn) can be even faster than O(nlogn) algorithms (w>logn), and is a very useful tool to know. It is used where there is basically nothing more to optimize, but is an interesting idea. The following is a source code from StackOverflow, a recursive implementation. 

There are many different variations, such as the Least Significant Digit Radix sort, which is a very stable sorting mechanism.

There is a visualization on the website
https://www.cs.usfca.edu/~galles/visualization/RadixSort.html

Overall, I see myself using this algorithm often.

Source Code

void radixSort(int* input, int size, int digit)
{
    if (size == 0)return;
    int[10] buckets;
    for (int i = 0; i <10;++i)radixSort(input + buckets[i], buckets[i+1] - buckets[i], digit+1);
}

Radix sort uses a length based type of comparison, and has a time complexity of O(wn), where w is the length of the data. For cases where w is constant, and n is very large, the complexity O(wn) can be even faster than O(nlogn) algorithms (w>logn), and is a very useful tool to know. It is used where there is basically nothing more to optimize, but is an interesting idea. The following is a source code from StackOverflow, a recursive implementation. 

There are many different variations, such as the Least Significant Digit Radix sort, which is a very stable sorting mechanism.

There is a visualization on the website
https://www.cs.usfca.edu/~galles/visualization/RadixSort.html

Overall, I see myself using this algorithm often.

Source Code

void radixSort(int* input, int size, int digit)
{
    if (size == 0)return;
    int[10] buckets;
    for (int i = 0; i <10;++i)radixSort(input + buckets[i], buckets[i+1] - buckets[i], digit+1);
}