As functional programmers we always face a dilemma: should we write purely functional code, or sacrifice purity for efficiency and resort to in-place updates? This paper identifies precisely when we can have the best of both worlds: a wide class of purely functional programs can be executed safely using in-place updates without requiring allocation, provided their arguments are not shared elsewhere. We describe a linear _fully in-place_ (FIP) calculus where we prove that we can always execute such functions in a way that requires no (de)allocation and uses constant stack space. Of course, such a calculus is only relevant if we can express interesting algorithms; we provide numerous examples of in-place functions on datastructures such as splay trees or finger trees, together with in-place versions of merge sort and quick sort. We also show how we can generically derive a map function over _any_ polynomial data type that is fully in-place. Finally, we have implemented the rules of the FIP calculus in the Koka language. Using the Perceus reference counting garbage collection, this implementation dynamically executes FIP functions in-place whenever possible.

@article{paperbot1911,
  title = {FP²: Fully in-Place Functional Programming},
  author = {Anton Lorenzen and Daan Leijen and Wouter Swierstra},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {7},
  number = {ICFP},
  year = {2023},
  doi = {10.1145/3607840}
}