Profil

JAHIC Benjamin

Main Referenced Co-authors
GUELFI, Nicolas  (7)
RIES, Benoit  (7)
Main Referenced Keywords
software engineering (4); Software Engineering (3); deep learning (2); domain-specific language (2); key-properties (2);
Main Referenced Disciplines
Computer science (10)

Publications (total 10)

The most downloaded
346 downloads
Jahic, B. (2016). TESMA : Requirements, Design and Implementation of a Teaching Specification, Management and Assessment tool [Bachelor/master dissertation, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/29884 https://hdl.handle.net/10993/29884

The most cited

8 citations (Scopus®)

Ries, B., Guelfi, N., & Jahic, B. (2021). An MDE Method for Improving Deep Learning Dataset Requirements Engineering using Alloy and UML. In Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development (pp. 41-52). SCITEPRESS. doi:10.5220/0010216600410052 https://hdl.handle.net/10993/45161

Jahic, B., Guelfi, N., & Ries, B. (01 April 2023). SEMKIS-DSL: A Domain-Specific Language to Support Requirements Engineering of Datasets and Neural Network Recognition. Information, 14 (4). doi:10.3390/info14040213
Peer Reviewed verified by ORBi

Jahic, B. (2022). SEMKIS: A CONTRIBUTION TO SOFTWARE ENGINEERING METHODOLOGIES FOR NEURAL NETWORK DEVELOPMENT [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/50986

Jahic, B., Guelfi, N., & Ries, B. (2021). SEMKIS-DSL: a Domain-Specific Language for Specifying Neural Networks’ Key-Properties. Belval, Luxembourg: Lassy.

Ries, B., Guelfi, N., & Jahic, B. (2021). An MDE Method for Improving Deep Learning Dataset Requirements Engineering using Alloy and UML. In Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development (pp. 41-52). SCITEPRESS. doi:10.5220/0010216600410052
Peer reviewed

Jahic, B., Guelfi, N., & Ries, B. (2020). Specifying key-properties to improve the recognition skills of neural networks. In Proceedings of the 2020 European Symposium on Software Engineering. New York, United States: Association for Computing Machinery. doi:10.1145/3393822.3432332
Peer reviewed

Jahic, B., Guelfi, N., & Ries, B. (2019). Software Engineering for Dataset Augmentation using Generative Adversarial Networks. In Proceedings of 10th IEEE International Conference on Software Engineering and Service Science. doi:10.1109/ICSESS47205.2019.9040806
Peer reviewed

Jahic, B. (2018). SEMKIS : Software Engineering Methodology for Knowledge Management of Intelligent Systems. Belval, Luxembourg: Laboratory for Advanced Software Systems.

Guelfi, N., Jahic, B., & Ries, B. (2017). TESMA: Requirements and Design of a Tool for Educational Programs. Information. doi:10.3390/info8010037
Peer Reviewed verified by ORBi

Guelfi, N., Jahic, B., & Ries, B. (2016). TESMA : Towards the Development of a Tool for Specification, Management and Assessment of Teaching Programs. In E. Pyshkin, A. Vazhenin, ... V. Klyuev (Eds.), Proceeding of the 2nd International Conference on Applications in Information Technology (pp. 5-8). Aizuwakamazsu, Japan: The University of Aizu Press.
Peer reviewed

Jahic, B. (2016). TESMA : Requirements, Design and Implementation of a Teaching Specification, Management and Assessment tool [Bachelor/master dissertation, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/29884

Contact ORBilu