From Temporal Models to Property-Based Testing
May 29, 2017 Β· Declared Dead Β· π International Conference on Evaluation of Novel Approaches to Software Engineering
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Nasser Alzahrani, Maria Spichkova, Jan Olaf Blech
arXiv ID
1705.10032
Category
cs.SE: Software Engineering
Citations
9
Venue
International Conference on Evaluation of Novel Approaches to Software Engineering
Last Checked
4 months ago
Abstract
This paper presents a framework to apply property-based testing (PBT) on top of temporal formal models. The aim of this work is to help software engineers to understand temporal models that are presented formally and to make use of the advantages of formal methods: the core time-based constructs of a formal method are schematically translated to the BeSpaceD extension of the Scala programming language. This allows us to have an executable Scala code that corresponds to the formal model, as well as to perform PBT of the models functionality. To model temporal properties of the systems, in the current work we focus on two formal languages, TLA+ and FocusST.
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