| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
aCHAT-WF: Generating conversational agents for teaching business process models
|
Rooein, Donya
|
|
|
21 |
3 |
p. 891-914
|
artikel
|
| 2 |
A generic approach to detect design patterns in model transformations using a string-matching algorithm
|
Mokaddem, Chihab eddine
|
|
|
21 |
3 |
p. 1241-1269
|
artikel
|
| 3 |
AI-driven streamlined modeling: experiences and lessons learned from multiple domains
|
Sunkle, Sagar
|
|
|
21 |
3 |
p. 1-23
|
artikel
|
| 4 |
AI-powered model repair: an experience report—lessons learned, challenges, and opportunities
|
Barriga, Angela
|
|
|
21 |
3 |
p. 1135-1157
|
artikel
|
| 5 |
A model-driven approach to machine learning and software modeling for the IoT
|
Moin, Armin
|
|
|
21 |
3 |
p. 987-1014
|
artikel
|
| 6 |
Analysing factors impacting BPMS performance: a case of a challenged technology adoption
|
Seymour, Lisa F.
|
|
|
21 |
3 |
p. 869-890
|
artikel
|
| 7 |
An exception handling framework for case management
|
Andree, Kerstin
|
|
|
21 |
3 |
p. 939-962
|
artikel
|
| 8 |
Automated, interactive, and traceable domain modelling empowered by artificial intelligence
|
Saini, Rijul
|
|
|
21 |
3 |
p. 1015-1045
|
artikel
|
| 9 |
DEVS-based formalism for the modeling of routing processes
|
Blas, María Julia
|
|
|
21 |
3 |
p. 1179-1208
|
artikel
|
| 10 |
Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning
|
Parra-Ullauri, Juan Marcelo
|
|
|
21 |
3 |
p. 1091-1113
|
artikel
|
| 11 |
Explicit versus implicit models: What are good languages for modeling?
|
Gray, Jeff
|
|
|
21 |
3 |
p. 839-841
|
artikel
|
| 12 |
Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning
|
Dehghani, MohammadHadi
|
|
|
21 |
3 |
p. 1115-1133
|
artikel
|
| 13 |
Guest editorial to the theme section on AI-enhanced model-driven engineering
|
Burgueño, Lola
|
|
|
21 |
3 |
p. 963-965
|
artikel
|
| 14 |
Interactive log-delta analysis using multi-range filtering
|
Vidgof, Maxim
|
|
|
21 |
3 |
p. 847-868
|
artikel
|
| 15 |
Model-based ideal testing of hardware description language (HDL) programs
|
Kilincceker, Onur
|
|
|
21 |
3 |
p. 1209-1240
|
artikel
|
| 16 |
ModelSet: a dataset for machine learning in model-driven engineering
|
López, José Antonio Hernández
|
|
|
21 |
3 |
p. 967-986
|
artikel
|
| 17 |
On the adoption of blockchain for business process monitoring
|
Di Ciccio, Claudio
|
|
|
21 |
3 |
p. 915-937
|
artikel
|
| 18 |
Promoting social diversity for the automated learning of complex MDE artifacts
|
Batot, Edouard R.
|
|
|
21 |
3 |
p. 1159-1178
|
artikel
|
| 19 |
Recommending metamodel concepts during modeling activities with pre-trained language models
|
Weyssow, Martin
|
|
|
21 |
3 |
p. 1071-1089
|
artikel
|
| 20 |
Special section of BPMDS’2020 business process management meets data
|
Soffer, Pnina
|
|
|
21 |
3 |
p. 843-845
|
artikel
|
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