Using Off-the-Shelf Exception Support Components in C++ Verification
March 07, 2017 Β· Declared Dead Β· π International Conference on Software Quality, Reliability and Security
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
VladimΓr Ε till, Petr RoΔkai, JiΕΓ Barnat
arXiv ID
1703.02394
Category
cs.SE: Software Engineering
Cross-listed
cs.PL
Citations
7
Venue
International Conference on Software Quality, Reliability and Security
Last Checked
4 months ago
Abstract
An important step toward adoption of formal methods in software development is support for mainstream programming languages. Unfortunately, these languages are often rather complex and come with substantial standard libraries. However, by choosing a suitable intermediate language, most of the complexity can be delegated to existing execution-oriented (as opposed to verification-oriented) compiler frontends and standard library implementations. In this paper, we describe how support for C++ exceptions can take advantage of the same principle. Our work is based on DiVM, an LLVM-derived, verification-friendly intermediate language. Our implementation consists of 2 parts: an implementation of the `libunwind` platform API which is linked to the program under test and consists of 9 C functions. The other part is a preprocessor for LLVM bitcode which prepares exception-related metadata and replaces associated special-purpose LLVM instructions.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
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