Mutable value semantics is a programming discipline that upholds the independence of values to support local reasoning. In the discipline’s strictest form, references become second-class citizens: they are only created implicitly, at function boundaries, and cannot be stored in variables or object fields. Hence, variables can never share mutable state. Unlike pure functional programming, however, mutable value semantics allows part-wise in-place mutation, thereby eliminating the memory traffic usually associated with functional updates of immutable data.
This paper presents implementation strategies for compiling programs with mutable value semantics into efficient native code. We study Swift, a programming language based on that discipline, through the lens of a core language that strips some of Swift’s features to focus on the semantics of its value types. The strategies that we introduce leverage the inherent properties of mutable value semantics to unlock aggressive optimizations. Fixed-size values are allocated on the stack, thereby enabling numerous off-the-shelf compiler optimizations, while dynamically sized containers use copy-on-write to mitigate copying costs.