@inproceedings{10.1145/3550356.3561542,
author = {Cabot, Jordi and Delgado, David and Burgue\~{n}o, Lola},
title = {Combining OCL and natural language: a call for a community effort},
year = {2022},
isbn = {9781450394673},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3550356.3561542},
doi = {10.1145/3550356.3561542},
abstract = {The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation of code excerpts from NL instructions or the verbalization of programs in NL to facilitate their comprehension.Many of these language models have been trained with open source software datasets and therefore "understand" a variety of programming languages, but not OCL.We argue that OCL needs to jump into the machine learning bandwagon or it will risk losing its appeal as a constraint specification language. For that, the key first task is to create together an OCL corpus dataset amenable for natural language processing.},
booktitle = {Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings},
pages = {908–912},
numpages = {5},
keywords = {OCL, community, corpus, dataset, natural language},
location = {Montreal, Quebec, Canada},
series = {MODELS '22}
}