Flexible Model-to-Model Transformation Templates: An Application to ATL.

Cuadrado, Jesús Sánchez; Guerra, Esther; Lara, Juan de

doi:10.5381/jot.2012.11.2.a4

Cited by 7 publications

(3 citation statements)

References 28 publications

(22 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is a structure-preserving mapping b : C → T relating each class, attribute, and reference of the context meta-model C to elements of the target meta-model T . We closely follow [36], [52] for the definition of its well-formedness conditions:…”

Section: B the Bindingmentioning

confidence: 99%

Model Sensemaking Strategies: Exploiting Meta-Model Patterns to Understand Large Models

Martínez-Lasaca,

Díez,

Guerra

et al. 2023

2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)

Self Cite

View full text Add to dashboard Cite

The increasing popularity of model-based and lowcode platforms has raised the need to understand large models -especially in industrial settings. However, current approaches mainly rely on graph-based visual metaphors, which do not scale well with large model sizes. To address this issue, we introduce model sensemaking strategies: purposeful model visualisations based on alternative visual metaphors. We define them as reusable patterns that yield tailored visualisations when applied to meta-models. This paper presents a catalogue of domain-specific and domain-agnostic sensemaking strategies, and a recommender that suggests suitable strategies for a given meta-model. To showcase the framework's applicability, we have implemented some of these strategies in Dandelion, an industrial, low-code graphical language workbench for the cloud. Using this platform, we have evaluated the effectiveness of the strategies to visualise large industrial models by the UGROUND company.

show abstract

Section: B the Bindingmentioning

confidence: 99%

Model Sensemaking Strategies: Exploiting Meta-Model Patterns to Understand Large Models

Martínez-Lasaca,

Díez,

Guerra

et al. 2023

2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The possibility of XMI-based generic transformations of UML models is examined in Jiménez et al [13]. Cuadrado et al [3] gives an approach to present the generic programming transformation template for reusable. Kovse et al [14] provides a method to make the model-driven development of RubyTL model transformations easier.…”

Section: Related Workmentioning

confidence: 99%

Automatic Generation of the AADL ALISA Verification Plan with ATL

Wu¹,

Huang²,

Yang³

et al. 2017

IJPE

View full text Add to dashboard Cite

Architecture Led Incremental System Assurance short for ALISA presents a method to check if a system implementation meets its requirements. This method helps find errors in the early phase of system integration. ALISA provides four notations-requirements specifications, architecture models, verification techniques and assurance cases. The verification plan, which is designed by extracting information from requirement specification and architecture model, can be executed on the system and the result is significant metrics to judge the system quality. There are problems when generating a verification plan. As for the hierarchical architecture model with increasing complexity, the system may be divided into several parts and it is difficult to accomplish the assurance manually for each tier of the architecture. The approach also needs to respond to the ever-changing demands rapidly. New faults may be introduced artificially when designing requirement specifications and verification plans. In the paper, we propose an approach which uses ATL, whose full name is ATLAS transformation language, to help automatically generate verification plans. The meta-model of the verification plan and of requirement specification are given. Thus, designing the transformation rules from the verification part to the requirement part is easy. A lightweight template described in ATL is used to generate the verification plan for critical requirement and quality property.

show abstract

“…GTS transformers, and the GTS families we generate with them, generalise the idea of adapters over transformations (also called adaptations in [13,23,24]). We start by defining GTS transformers as transformations between GTSs.…”

Section: Gts Transformersmentioning

confidence: 99%

GTS Families for the Flexible Composition of Graph Transformation Systems

Zschaler

Durán

2017

Fundamental Approaches to Software Engineering

View full text Add to dashboard Cite

Abstract. Morphisms between graph-transformation systems (GTSs) have been successfully used for the refinement, reuse, and composition of GTSs. All these uses share a fundamental problem: to be able to define a morphism, source and target GTSs need to be quite similar in their structure (in terms of both the type graphs and the set of rules and their respective structures). This limits the applicability of these approaches by excluding a wide range of mappings that would intuitively be accepted as meaningful, but that cannot be captured formally as a morphism. Some researchers have attempted to introduce some flexibility, but these attempts either focus only on the type graphs (e.g., Kleisli morphisms between type graphs) or only support specific forms of deviation (e.g., supporting sub-typing in type graphs through clan morphisms). In this work, we introduce the notion of GTS families, which provide a general mechanism for explicitly expressing the amount of acceptable adaptability of the involved GTSs so that the intended morphisms can be defined. On this basis, we demonstrate how GTS families that are extension preserving can be used to enable flexible GTS amalgamation.

show abstract

Flexible Model-to-Model Transformation Templates: An Application to ATL.

Cited by 7 publications

References 28 publications

Model Sensemaking Strategies: Exploiting Meta-Model Patterns to Understand Large Models

Model Sensemaking Strategies: Exploiting Meta-Model Patterns to Understand Large Models

Automatic Generation of the AADL ALISA Verification Plan with ATL

GTS Families for the Flexible Composition of Graph Transformation Systems

Contact Info

Product

Resources

About