Automated, interactive, and traceable domain modelling empowered by artificial intelligence

Author:

Saini Rijul,Mussbacher Gunter,Guo Jin L. C.,Kienzle Jörg

Publisher

Springer Science and Business Media LLC

Subject

Modeling and Simulation,Software

Reference49 articles.

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2. Arora, C., Sabetzadeh, M., Briand, L., Zimmer, F.: Extracting domain models from natural-language requirements: Approach and industrial evaluation. In: Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems, MODELS ’16, p. 250-260. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2976767.2976769

3. Ben Charrada, E., Caspar, D., Jeanneret, C., Glinz, M.: Towards a benchmark for traceability. In: Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Software Evolution, IWPSE-EVOL ’11, p. 21–30. Association for Computing Machinery, New York, NY, USA (2011). https://doi.org/10.1145/2024445.2024451

4. Bencomo, N., Garcia Paucar, L.H.: RaM: causally-connected and requirements-aware runtime models using Bayesian learning. In: 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS), pp. 216–226 (2019). https://doi.org/10.1109/MODELS.2019.00005

5. Bousse, E., Mayerhofer, T., Combemale, B., Baudry, B.: A generative approach to define rich domain-specific trace metamodels. In: 11th European Conference on Modelling Foundations and Applications (ECMFA). L’Aquila, Italy (2015). https://hal.inria.fr/hal-01154225

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