A Formalization Model Transformation Approach on Workflow Automatic Execution from CIM Level to PIM Level

Li, Zonghua; Zhou, Xiaofeng; Ye, Zhengwei

doi:10.1142/s0218194019500372

Cited by 6 publications

(2 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This transformation includes four rules, two negative preconditions, two negative postconditions, and no negative invariant; B2P. The BPMN2PetriNet transformation [49] transforms BPMN models at the Computational Independent Model (CIM) level to PetriNet models at the Platform Independent Model (PIM) level. This model transformation includes twelve rules, five negative preconditions, two negative postconditions, and no negative invariant.…”

Section: C2r the Cd2rdbm Transformation [46] Is Implementedmentioning

confidence: 99%

On integrating multiple restriction domains to automatically generate test cases of model transformations

Nguyen

Dang

2023

IJCAI

View full text Add to dashboard Cite

Testing model transformations poses several challenges, one of which is how to automatically generate effective test suites. A promising approach for this is to employ equivalence partitioning, a well-known technique for software testing. Specifically, in order to generate effective test suites, current works in literature often focus on exploiting either the structural aspects of models or transformation contracts for partition analysis. However, for the aim, they focus on only a single restriction source such as metamodels, contracts of the transformation, and domain-expert knowledge. To increase the effectiveness of generated test suites, partitioning techniques should be performed on a combination of various restriction sources. This paper introduces a method to generate test models on such a multi-domain of restrictions. The method also allows the tester to flexibly select and combine constraints to create a unified restriction for different strategies and objectives in model transformation testing. We developed a support tool based on the UMLbased Specification Environment (USE) and performed experiments on several transformations to point out the effectiveness of our method.Povzetek: Opisana je metoda preverjanja programske kode na osnovi multi-modalnih omejitev posameznih delov.

show abstract

Section: C2r the Cd2rdbm Transformation [46] Is Implementedmentioning

confidence: 99%

On integrating multiple restriction domains to automatically generate test cases of model transformations

Nguyen

Dang

2023

IJCAI

View full text Add to dashboard Cite

show abstract

“…Labanotation has also investigated the use of computers for drawing and displaying. Literature [9] used motion capture equipment to collect data from a 41-point model, emphatically analyzing movements such as rotation, pace, jumping, lifting, and descending, and the Laban Writer output dance music through the interface, so the movements studied lacked universality. Literature [10] analyzes the supporting and unsupported actions separately and proposes a method of automatically generating labanotation based on knowledge rules, which details each part of the method and realizes the platform of automatically generating labanotation, according to the labanotation analysis principle.…”

Section: Related Workmentioning

confidence: 99%

A Motion Capture Data-Driven Automatic Labanotation Generation Model Using the Convolutional Neural Network Algorithm

Jiang

Yang

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

All human movements can be effectively represented with labanotation, which is simple to read and preserve. However, manually recording the labanotation takes a long time, so figuring out how to use the labanotation to accurately and quickly record and preserve traditional dance movements is a key research question. An automatic labanotation generation algorithm based on DL (deep learning) is proposed in this study. The BVH file is first analyzed, and the data are then converted. On this foundation, a CNN (convolutional neural network) algorithm for generating the dance spectrum of human lower-limb movements is proposed, which is very good at learning action space information. The algorithm performs admirably in terms of classification and recognition. Finally, a spatial segmentation-based automatic labanotation generation algorithm is proposed. To begin, every frame of data is converted into a symbol sequence using spatial law, resulting in a very dense motion sequence. The motion sequence is then regulated according to the minimum beat of motion obtained through wavelet analysis. To arrive at the final result, the classifier is used to determine whether each symbol is reserved or not. As a result, we will be able to create more accurate dance music for simple human movements.

show abstract

Combining a Domain Ontology and MDD Technologies to Create and Validate Business Process Models

Silega,

Noguera,

Rogozov

et al. 2024

Proceedings of the I-Esa Conferences

View full text Add to dashboard Cite

A Formalization Model Transformation Approach on Workflow Automatic Execution from CIM Level to PIM Level

Cited by 6 publications

References 46 publications

On integrating multiple restriction domains to automatically generate test cases of model transformations

On integrating multiple restriction domains to automatically generate test cases of model transformations

A Motion Capture Data-Driven Automatic Labanotation Generation Model Using the Convolutional Neural Network Algorithm

Combining a Domain Ontology and MDD Technologies to Create and Validate Business Process Models

Contact Info

Product

Resources

About