Distilling Abstract Machines (Long Version)
Beniamino Accattoli, Pablo Barenbaum, Damiano Mazza

TL;DR
This paper explores how the linear substitution calculus (LSC) can distill environment-based abstract machines, revealing their implementation of weak linear head reduction and preserving execution complexity across various evaluation strategies.
Contribution
It introduces a novel distillation process that relates abstract machines to the LSC, unifying different evaluation strategies and demonstrating complexity preservation.
Findings
LSC distills various abstract machines, simplifying their transitions.
Abstract machines implement weak linear head reduction.
Distillation preserves the time complexity of executions.
Abstract
It is well-known that many environment-based abstract machines can be seen as strategies in lambda calculi with explicit substitutions (ES). Recently, graphical syntaxes and linear logic led to the linear substitution calculus (LSC), a new approach to ES that is halfway between big-step calculi and traditional calculi with ES. This paper studies the relationship between the LSC and environment-based abstract machines. While traditional calculi with ES simulate abstract machines, the LSC rather distills them: some transitions are simulated while others vanish, as they map to a notion of structural congruence. The distillation process unveils that abstract machines in fact implement weak linear head reduction, a notion of evaluation having a central role in the theory of linear logic. We show that such a pattern applies uniformly in call-by-name, call-by-value, and call-by-need, catching…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLogic, programming, and type systems · Parallel Computing and Optimization Techniques · Computability, Logic, AI Algorithms
