Fully-Automatic Type Inference for Borrows with Lifetimes
William Brandon, Benjamin Driscoll, Frank Dai, Jonathan Ragan-Kelley, Mae Milano, Alex Aiken
摘要
We present a new pure functional language and type system with borrows with lifetimes, and a corresponding fully-automatic type inference procedure. Inference provides users the performance benefits of borrows with lifetimes without requiring user annotation. If the user’s program cannot be typed, inference inserts a handful of reference count operations so that it can be typed. We provide a heap semantics for our borrowing language and prove a soundness theorem, guaranteeing that well-typed programs do not violate memory safety. We implement our memory management strategy as part of the Morphic language stack and compare it to Perceus, a state-of-the-art reference-counting technique based on linear type inference. We find that our system is able to eliminate almost all reference count operations across a range of programs, reducing reference count increments by 75–100% on all benchmarks with reference count increments under the baseline. As a result, we achieve a 1 . 48× geomean speedup overall on all benchmarks.
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