We extend the semantics and type system of a lambda calculus equipped with common constructs to be \emph{resource-aware}. That is, reduction is instrumented to keep track of the usage of resources, and the type system guarantees, besides standard soundness, that for well-typed programs there is a computation where no needed resource gets exhausted.
The resource-aware extension is parametric on an arbitrary \emph{grade algebra}, and does not require ad-hoc changes to the underlying language. To this end, the semantics needs to be formalized in big-step style; as a consequence, expressing and proving (resource-aware) soundness is challenging, and is achieved by applying recent techniques based on coinductive reasoning.
Thu 26 OctDisplayed time zone: Lisbon change
Thu 26 Oct
Displayed time zone: Lisbon change
11:00 - 12:30 | |||
11:00 18mTalk | Reference Capabilities for Flexible Memory Management OOPSLA Ellen Arvidsson Uppsala University, Elias Castegren Uppsala University, Sylvan Clebsch Microsoft Azure Research, Sophia Drossopoulou Imperial College London, James Noble Research & Programming, Matthew J. Parkinson Microsoft Azure Research, Tobias Wrigstad Uppsala University DOI Pre-print | ||
11:18 18mTalk | A Grounded Conceptual Model for Ownership Types in Rust OOPSLA DOI Pre-print | ||
11:36 18mTalk | Inference of Resource Management Specifications OOPSLA Narges Shadab University of California at Riverside, PRITAM MANOHAR GHARAT Microsoft Research, Shrey Tiwari Microsoft Research, Michael D. Ernst University of Washington, Martin Kellogg New Jersey Institute of Technology, Shuvendu K. Lahiri Microsoft Research, Akash Lal Microsoft Research, Manu Sridharan University of California at Riverside DOI | ||
11:54 18mTalk | Resource-Aware Soundness for Big-Step Semantics OOPSLA Riccardo Bianchini University of Genoa, Francesco Dagnino University of Genoa, Paola Giannini University of Eastern Piedmont, Elena Zucca University of Genoa DOI | ||
12:12 18mTalk | Verus: Verifying Rust Programs using Linear Ghost Types OOPSLA Andrea Lattuada VMware Research, Travis Hance Carnegie Mellon University, Chanhee Cho Carnegie Mellon University, Matthias Brun ETH Zurich, Isitha Subasinghe UNSW Sydney, Yi Zhou Carnegie Mellon University, Jon Howell VMware Research, Bryan Parno Carnegie Mellon University, Chris Hawblitzel Microsoft Research DOI |