FP^2: Fully in-Place Functional Programming - Lorenzen, Anton; Leijen, Daan; Swierstra, Wouter (ICFP 2023, 2023)
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.
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