Typing Requirement Model as Coroutines
May 16, 2024 Β· Declared Dead Β· π IEEE Access
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Qiqi Gu, Wei Ke
arXiv ID
2405.10060
Category
cs.SE: Software Engineering
Cross-listed
cs.PL
Citations
2
Venue
IEEE Access
Last Checked
4 months ago
Abstract
Model-Driven Engineering (MDE) is a technique that aims to boost productivity in software development and ensure the safety of critical systems. Central to MDE is the refinement of high-level requirement models into executable code. Given that requirement models form the foundation of the entire development process, ensuring their correctness is crucial. RM2PT is a widely used MDE platform that employs the REModel language for requirement modeling. REModel contains contract sections and other sections including a UML sequence diagram. This paper contributes a coroutine-based type system that represents pre- and post-conditions in the contract sections in a requirement model as the receiving and yielding parts of coroutines, respectively. The type system is capable of composing coroutine types, so that users can view functions as a whole system and check their collective behavior. By doing so, our type system ensures that the contracts defined in it are executed as outlined in the accompanied sequence diagram. We assessed our approach using four case studies provided by RM2PT, validating the accuracy of the models.
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