An in-place algorithm is an algorithm that transforms the input data structure without using extra data structures for storage. It operates directly on the input, modifying it as necessary, while using only a constant amount of extra space for variables.

The key characteristic of in-place algorithms is their space efficiency. They typically have a space complexity of O(1) or constant space, meaning the amount of additional memory they use doesn't grow with the size of the input.

In-place algorithms are particularly valuable in environments with limited memory resources, when working with very large datasets, or when memory allocation and deallocation operations are expensive.

Some algorithms can be implemented in either in-place or out-of-place variants, with different trade-offs in terms of simplicity, speed, and memory usage. In-place versions generally save space but might be more complex or slightly slower in some cases.

Characteristics of in-place algorithms:

• Use minimal extra memory beyond the input itself
• Typically modify the input structure directly
• Often use techniques like swapping elements or overwriting values
• May use a small constant amount of extra space for temporary variables