Detecting lifetime errors of std::string_view objects in C++
August 18, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Reka Kovacs, Gabor Horvath, Zoltan Porkolab
arXiv ID
2408.09325
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
std::string view is a reference-like data structure in the C++ Standard Template Library (STL) that enables fast and cheap processing of read-only strings. Due to its wide applicability and performance enhancing power, std::string view has been very popular since its introduction in the C++17 standard. However, its careless use can lead to serious memory management bugs. As the lifetime of a std::string view is not tied to the lifetime of the referenced string in any way, it is the user's responsibility to ensure that the view is only used while the viewed string is live and its buffer is not reallocated. This paper describes a static analysis tool that finds programming errors caused by the incorrect use of std::string view. Our work included modeling std::string view operations in the analysis, defining steps to detect lifetime errors, constructing user-friendly diagnostic messages, and performing an evaluation of the checker.
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