InPlace

In computer science, in-place refers to operations or algorithms that transform data using little or no extra space beyond a constant amount of auxiliary memory. An in-place algorithm modifies the input data directly and may write results back into the same data structure, rather than producing a separate, largely independent output.

The defining characteristic of in-place work is the space complexity, typically O(1) additional space. This can be contrasted with out-of-place algorithms that allocate memory proportional to the input size to store the results. In practice, some in-place algorithms still use recursion, which consumes stack space, so the effective extra space may be more than constant unless an iterative approach is used.

Common examples include reversing an array by swapping elements, rotating an array with a series of element swaps, or partitioning data in quicksort in place. In-place editing is also common in string and array transformations, such as removing duplicates or shifting elements to fill gaps. The trade-offs for in-place methods often include increased implementation complexity, potential reductions in readability, and, in some cases, reduced stability in sorting.

Variants and related concepts include stable in-place sorts, which achieve stability without allocating extra storage, albeit with additional algorithmic complexity. The term is sometimes used interchangeably with in situ, though in situ can have broader meanings in different domains. Understanding whether an operation is in-place involves considering both memory usage and how data is accessed and modified during execution.