We provide the code used to produce the analyses of our paper: Leveraging knowledge graphs for goal model generation. The code can be run in a dedicated Jupyter Notebook:
pip install -r requirements.txt
jupyter notebook approach_demo.ipynb
@inproceedings{abdoulsoukour:hal-04486653,
TITLE = {{Leveraging Knowledge Graphs for Goal Model Generation}},
AUTHOR = {Abdoul Soukour, Shahin and Aboucaya, William and Georgantas, Nikolaos},
URL = {https://inria.hal.science/hal-04486653},
BOOKTITLE = {{7th Workshop on Natural Language Processing for Requirements Engineering (NLP4RE) in conjuction with the 30th International Woking Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2024)}},
ADDRESS = {Winterthur, Switzerland},
EDITOR = {CEUR-WS},
PAGES = {11},
YEAR = {2024},
MONTH = Apr,
KEYWORDS = {Goal-oriented Requirements Engineering ; KAOS ; Domain Knowledge Graph ; Natural Language Processing ; Natural Language Inference},
PDF = {https://inria.hal.science/hal-04486653v2/file/_NLP4RE_24__NLP_for_goal_models_camera_ready_version.pdf},
HAL_ID = {hal-04486653},
HAL_VERSION = {v2},
}