We introduce Perceus, an algorithm for precise reference counting with
\nreuse and specialization. Starting from a functional core language with
\nexplicit control-flow, Perceus emits precise reference counting
\ninstructions such that programs are _garbage free_, where only live
\nreferences are retained. This enables further optimizations,
\nlike reuse analysis that allows for guaranteed in-place updates at
\nruntime. This in turn enables a novel programming paradigm that we call
\n_functional but in-place_ (FBIP). Much like tail-call optimization
\nenables writing loops with regular function calls, reuse analysis enables
\nwriting in-place mutating algorithms in a purely functional way. We give
\na novel formalization of reference counting in a linear resource
\ncalculus, and prove that Perceus is sound and garbage free. We show
\nevidence that Perceus, as implemented in Koka, has good performance
\nand is competitive with other state-of-the-art memory collectors.<\/p>\n","protected":false},"excerpt":{"rendered":"
We introduce Perceus, an algorithm for precise reference counting with reuse and specialization. Starting from a functional core language with explicit control-flow, Perceus emits precise reference counting instructions such that programs are _garbage free_, where only live references are retained. This enables further optimizations, like reuse analysis that allows for guaranteed in-place updates at runtime. 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