Correctness Witnesses with Function Contracts
January 21, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Matthias Heizmann, Dominik Klumpp, Marian Lingsch-Rosenfeld, Frank SchΓΌssele
arXiv ID
2501.12313
Category
cs.PL: Programming Languages
Cross-listed
cs.SE
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Software verification witnesses are a common exchange format for software verification tools. They were developed to provide arguments supporting the verification result, allowing other tools to reproduce the verification results. Correctness witnesses in the current format (version 2.0) allow only for the encoding of loop and location invariants using C expressions. This limits the correctness arguments that verifiers can express in the witness format. One particular limitation is the inability to express function contracts, which consist of a pre-condition and a post-condition for a function. We propose an extension to the existing witness format 2.0 to allow for the specification of function contracts. Our extension includes support for several features inspired by ACSL (\result, \old, \at). This allows for the export of more information from tools and for the exchange of information with tools that require function contracts.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Programming Languages
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
R.I.P.
π»
Ghosted
Glow: Graph Lowering Compiler Techniques for Neural Networks
R.I.P.
π»
Ghosted
Learnable Programming: Blocks and Beyond
R.I.P.
π»
Ghosted
Scenic: A Language for Scenario Specification and Scene Generation
R.I.P.
π»
Ghosted
Vandal: A Scalable Security Analysis Framework for Smart Contracts
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted