Verifying Patterns of Dynamic Architectures using Model Checking
March 21, 2017 Β· Declared Dead Β· π EPTCS 245, 2017, pp. 16-30
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Diego Marmsoler, Silvio Degenhardt
arXiv ID
1703.07033
Category
cs.SE: Software Engineering
Citations
0
Venue
EPTCS 245, 2017, pp. 16-30
Last Checked
5 months ago
Abstract
Architecture patterns capture architectural design experience and provide abstract solutions to recurring architectural design problems. They consist of a description of component types and restrict component connection and activation. Therefore, they guarantee some desired properties for architectures employing the pattern. Unfortunately, most documented patterns do not provide a formal guarantee of whether their specification indeed leads to the desired guarantee. Failure in doing so, however, might lead to wrong architectures, i.e., architectures wrongly supposed to show certain desired properties. Since architectures, in general, have a high impact on the quality of the resulting system and architectural flaws are only difficult, if not to say impossible, to repair, this may lead to badly reparable quality issues in the resulting system. To address this problem, we propose an approach based on model checking to verify pattern specifications w.r.t. their guarantees. In the following we apply the approach to three well-known patterns for dynamic architectures: the Singleton, the Model-View-Controller, and the Broker pattern. Thereby, we discovered ambiguities and missing constraints for all three specifications. Thus, we conclude that verifying patterns of dynamic architectures using model checking is feasible and useful to discover ambiguities and flaws in pattern specifications.
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