Model driven transformation development (MDTD): An approach for developing model to model transformation

Magalhães, Ana Patrícia; Andrade, Adnei Melges de; Maciel, Rita Suzana Pitangueira

doi:10.1016/j.infsof.2019.06.004

Cited by 10 publications

(5 citation statements)

References 13 publications

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“…Thus, we took advantage of Eclipse's model management technologies, Eclipse Modelling Framework (EMF). We used model-to-model approach [26], and therefore, we used two meta-models, where one metamodel represents KAOS method and the other represents Event-B method.…”

Section: A Rule Definitionmentioning

confidence: 99%

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Keep All Objectives Satisfied (KAOS) to Event-B Models Transformation

Saharudin¹,

Said²

2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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Requirements engineering is an important aspect of the software development methodology because it is the first phase in every software development. The usefulness of formal language in requirements is well-established to ensure consistency. However, the conversion from informal requirements to the formal specification phase is still challenging because it requires advanced skills and much practice. Due to this challenge, we improve the conversion and relationship of these two phases by capturing requirements using KAOS approach and writing the formal specification using Event-B language. KAOS approach allows modeling the requirements through goal hierarchies, whereas Event-B is a formal system-level modeling and analysis method. This work proposes model transformation rules from KAOS model to Event-B model, along with implementing the rules, and evaluates the proposed rules using Mine Pump Controller case study. We used a model-driven approach, specifically model-to-model transformation, to transform KAOS model to Event-B model. We modeled the case study into the KAOS model to obtain the source model for our model transformation and extend the existing KAOS meta-model by adding four new meta-classes to ensure the KAOS model can accommodate all Event-B components. Our proposed rules manage to generate an abstract Event-B model, and a set of proof obligations have been used to verify the correctness of the model. However, the designers must manually perform the transition between the generated outputs to the Event-B platform.

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Section: A Rule Definitionmentioning

confidence: 99%

“…The model is proved using a set of proof obligations (POs) that had been generated by Rodin platform. Proof obligations are used to ensure the consistency of a certain property in formal specification [26]. If we can prove the proof obligations, then that property in the specification is consistent.…”

Section: E Event-b Proof Obligationsmentioning

confidence: 99%

Keep All Objectives Satisfied (KAOS) to Event-B Models Transformation

Saharudin¹,

Said²

2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…From a technical perspective, dedicated translation mechanisms and algorithms will be required to raise the level of abstraction or granularity, e.g., by employing clustering algorithms in call or execution graphs obtained through system inspection to identify more coarse grained 'components' or 'processes'. Modelto-model transformation techniques [67] will be required to select and convert the relevant system information encoded in descriptors and domain-specific languages into the target abstractions. Although these mechanisms will be heterogeneous in nature, they should all contribute to a coherent system model that serves as an appropriate input for systemcentric threat analysis.…”

Section: B Research Agendamentioning

confidence: 99%

Threat modeling at run time: the case for reflective and adaptive threat management (NIER track)

Landuyt

Pasquale

Sion

et al. 2021

2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)

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Threat modeling is an analysis activity aimed at eliciting viable and realistic security and privacy threats in the design of a software-intensive system. Threat modeling allows for a by-design approach, mitigating problems before they arise and avoiding later costly development efforts.However, it mainly pays off in software construction approaches that rely on planned architectures, in which sources of threats can be anticipated beforehand. These axiomatic assumptions are, however, increasingly untrue in contemporary software development practices in which software systems evolve drastically in later stages. In addition, software-intensive systems are increasingly faced with uncertainty in their operational contexts, and these are nearly impossible to enumerate in early development stages.In this article, we first present the idea of reflective threat modeling, which involves the automated derivation of architectural system models from run-time and operational system artifacts, providing the threat modeler with an accurate and workable run-time inspection view of the system. We then outline and motivate the potential of adopting threat analysis models as a basis for holistic and adaptive threat management through integration of adaptive security and privacy technologies. This will enable systems to autonomously respond to emerging threats by dynamically activating dedicated controls or via run-time reconfiguration.

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“…Moradi et al [31] propose a framework that allows on services modeling, in a graphical environment, and transforming them into executable context web services. Fontes Magalhães et al [32] describe the iterative and incremental process that guides model-to-model transformation development from requirements specification to implementation. Jácome and de Lara [33] propose a mechanism that allows specifying customization and extension rules for meta-models.…”

Section: Related Workmentioning

confidence: 99%

Applying Model-Driven Engineering to Distributed Ledger Deployment

Górski

Bednarski

2020

IEEE Access

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Distributed Ledger Technology (DLT) enables data storage in a decentralized manner among collaborating parties. The software architecture of such solutions encompasses models placed in the relevant architectural views. A lot of research is devoted to smart contracts and consensus algorithms, which are realized by distributed applications and can be positioned within the Logical view. However, we see the need to provide modeling support for the Deployment view of distributed ledger solutions. Especially since the chosen DLT framework has a significant impact on implementation and deployment. Besides, consistency between models and configuration deployment scripts should be ensured. So, we have applied Model-Driven Engineering (MDE) that allows on the transformation of models into more detailed models, source code, or tests. We have proposed Unified Modeling Language (UML) stereotypes and tagged values for distributed ledger deployment modeling and placed them in the UML Profile for Distributed Ledger Deployment. We have also designed the UML2Deployment model-to-code transformation for the R3 Corda DLT framework. A UML Deployment model is the source whereas a Gradle Groovy deployment script is the target of the transformation. We have provided the complete solution by incorporating the transformation into the Visual Paradigm modeling tool. Furthermore, we have designed a dedicated plug-in to validate generated deployment scripts. In the paper, we have shown how to design transformation for generating deployment scripts for the R3 Corda DLT framework with the ability to switch to another one. INDEX TERMS Distributed Ledger, Model-Driven Engineering, Architectural views model 1+5, Deployment view, Unified Modeling Language extensibility mechanisms.

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Model driven transformation development (MDTD): An approach for developing model to model transformation

Cited by 10 publications

References 13 publications

Keep All Objectives Satisfied (KAOS) to Event-B Models Transformation

Keep All Objectives Satisfied (KAOS) to Event-B Models Transformation

Threat modeling at run time: the case for reflective and adaptive threat management (NIER track)

Applying Model-Driven Engineering to Distributed Ledger Deployment

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