In-place sorting algorithms are a special type of sorting that uses very little extra memory.

These algorithms only need a small amount of extra space as they sort the data, which is great because it means less memory is used.

When we say they have a space complexity of $O(1)$, it means they only require a constant amount of space, no matter how much data you have.

This is different from out-of-place sorting algorithms, like Merge Sort, which need more extra memory—about $O(n)$ more. This additional memory is used for other arrays to help with sorting.

Important Features of In-Place Sorting Algorithms:

1. Memory Efficiency:

   • Algorithms like Quick Sort and Heap Sort are examples of in-place sorting.
   • They work by using the same array to sort the data, which helps save space.

2. Performance:

   • In-place algorithms save space and can also work faster because they process data in smaller chunks that are close together in memory.

3. Usage Stats:

   • Research shows that almost 70% of sorting tasks in software programs prefer in-place algorithms.
   • This is because they are efficient and don’t use as many resources.

Using less extra memory makes in-place sorting algorithms a great choice in situations where memory is limited.

This is especially true in embedded systems and devices that have low memory available.