Simulation of UML graph classification model by using data preprocessing and convolutional neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Link
https://link.springer.com/content/pdf/10.1007/s11082-023-05921-3.pdf
Reference14 articles.
1. Adamu, A., Abdulrahman, S.M., Zainoon, W.M.N.W., et al.: Model matching: prediction of the influence of UML class diagram parameters during similarity assessment using artificial neural network[J]. Deep Learn Approaches Spoken Nat Language Process 2021, 97–109 (2021)
2. Agner, L.T.W., Soares, I.W., Stadzisz, P.C., et al.: A Brazilian survey on UML and model-driven practices for embedded software development[J]. J. Syst. Softw. 86(4), 997–1005 (2013)
3. Chren, S., Buhnova, B., Macak, M., et al.: Mistakes in UML diagrams: analysis of student projects in a software engineering course[C]. In: 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET). IEEE, pp. 100–109, (2019)
4. Gosala, B., Chowdhuri, S.R., Singh, J., et al.: Automatic classification of UML class diagrams using deep learning technique: convolutional neural network[J]. Appl. Sci. 11(9), 4267 (2021)
5. Munialo, S. W., Muketha, G. M., Omieno, K. K.: Automated feature extraction from UML images to measure SOA size [J] (2020).
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