{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T02:02:43Z","timestamp":1777946563827,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":66,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,9,22]]},"DOI":"10.1145\/3640310.3674085","type":"proceedings-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T13:38:07Z","timestamp":1727703487000},"page":"160-171","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Toward Intelligent Generation of Tailored Graphical Concrete Syntax"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8133-0199","authenticated-orcid":false,"given":"Meriem","family":"Ben Chaaben","sequence":"first","affiliation":[{"name":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2737-0952","authenticated-orcid":false,"given":"Oussama","family":"Ben Sghaier","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9336-7714","authenticated-orcid":false,"given":"Mouna","family":"Dhaouadi","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9404-6410","authenticated-orcid":false,"given":"Nafisa","family":"Elrasheed","sequence":"additional","affiliation":[{"name":"Polytechnique Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2646-4471","authenticated-orcid":false,"given":"Ikram","family":"Darif","sequence":"additional","affiliation":[{"name":"\u00c9cole de Technologie Sup\u00e9rieure, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7688-5120","authenticated-orcid":false,"given":"Imen","family":"Jaoua","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7558-1434","authenticated-orcid":false,"given":"Bentley","family":"Oakes","sequence":"additional","affiliation":[{"name":"Polytechnique Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6527-1651","authenticated-orcid":false,"given":"Eugene","family":"Syriani","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4927-2755","authenticated-orcid":false,"given":"Mohammad","family":"Hamdaqa","sequence":"additional","affiliation":[{"name":"Polytechnique Montr\u00e9al, Montr\u00e9al, Canada"}]}],"member":"320","published-online":{"date-parts":[[2024,9,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"L. Almonte et al. 2021. Automating the synthesis of recommender systems for modelling languages. In Software Language Engineering. 22--35.","DOI":"10.1145\/3486608.3486905"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"D. Amyot H. Farah and J. Roy. 2006. Evaluation of development tools for domain-specific modeling languages. In System Analysis and Modeling.","DOI":"10.1007\/11951148_12"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"I. Arawjo et al. 2023. ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing. arXiv preprint arXiv:2309.09128 (2023).","DOI":"10.1145\/3613904.3642016"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"S. Arulmohan M. Meurs and S. Mosser. 2023. Extracting domain models from textual requirements in the era of large language models. In Model Driven Engineering Languages and Systems Companion. IEEE 580--587.","DOI":"10.1109\/MODELS-C59198.2023.00096"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-008-0086-z"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2018.11.041"},{"key":"e_1_3_2_1_7_1","volume-title":"Slicing-Based Techniques for Visualizing Large Metamodels. In Working Conference on Software Visualization. 25--29","author":"Blouin A.","year":"2014","unstructured":"A. Blouin et al. 2014. Slicing-Based Techniques for Visualizing Large Metamodels. In Working Conference on Software Visualization. 25--29."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2015.02.007"},{"key":"e_1_3_2_1_9_1","volume-title":"International Conference on Software Engineering: New Ideas and Emerging Results. IEEE, 7--12","author":"Chaaben M. B.","unstructured":"M. B. Chaaben, L. Burgue\u00f1o, and H. Sahraoui. 2023. Towards using few-shot prompt learning for automating model completion. In International Conference on Software Engineering: New Ideas and Emerging Results. IEEE, 7--12."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-023-01117-1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"K. Chen et al. 2023. Automated Domain Modeling with Large Language Models: A Comparative Study. In Model Driven Engineering Languages and Systems. IEEE 162--172.","DOI":"10.1109\/MODELS58315.2023.00037"},{"key":"e_1_3_2_1_12_1","volume-title":"SyntaxMap: A Modeling Language for Capturing Requirements of Graphical DSML. In Asia-Pacific Software Engineering Conference","volume":"1","author":"Cho H.","unstructured":"H. Cho, J. Gray, and E. Syriani. 2012. SyntaxMap: A Modeling Language for Capturing Requirements of Graphical DSML. In Asia-Pacific Software Engineering Conference, Vol. 1. IEEE, 705--708."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3233\/AO-210255"},{"key":"e_1_3_2_1_14_1","volume-title":"India Software Engineering Conference. 165--174","author":"Deeptimahanti D.","unstructured":"D. Deeptimahanti and R. Sanyal. 2011. Semi-automatic generation of UML models from natural language requirements. In India Software Engineering Conference. 165--174."},{"key":"e_1_3_2_1_15_1","unstructured":"K. D. Dhole R. Chandradevan and E. Agichtein. 2023. An interactive query generation assistant using LLM-based prompt modification and user feedback. arXiv preprint arXiv:2311.11226 (2023)."},{"key":"e_1_3_2_1_16_1","volume-title":"Prompt engineering for ChatGPT: A quick guide to techniques, tips, and best practices. Authorea Preprints","author":"Ekin S.","year":"2023","unstructured":"S. Ekin. 2023. Prompt engineering for ChatGPT: A quick guide to techniques, tips, and best practices. Authorea Preprints (2023)."},{"key":"e_1_3_2_1_17_1","unstructured":"Fr\u00e9d\u00e9ric Fondement. 2007. Concrete syntax definition for modeling languages. Ph.D. thesis. Ecole Polytechnique de Lausanne."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"F. Fondement and T. Baar. 2005. Making Metamodels Aware of Concrete Syntax. In Model Driven Architecture - Foundations and Applications. Springer 190--204.","DOI":"10.1007\/11581741_15"},{"key":"e_1_3_2_1_19_1","volume-title":"The Essential Guide to User Interface Design: An Introduction to GUI Design Principles and Techniques. Number","author":"Galitz W. O.","unstructured":"W. O. Galitz. 2007. The Essential Guide to User Interface Design: An Introduction to GUI Design Principles and Techniques. Number 3rd Edition. Wiley.","edition":"3"},{"key":"e_1_3_2_1_20_1","volume-title":"Cognitive Dimensions of Notations. In People and Computers V. British Computer Society Workshop Series, 443--460","author":"Green T R G","year":"1989","unstructured":"T R G Green. 1989. Cognitive Dimensions of Notations. In People and Computers V. British Computer Society Workshop Series, 443--460."},{"key":"e_1_3_2_1_21_1","first-page":"1","article-title":"Conceptual Modeling and Large Language Models: Impressions From First Experiments With ChatGPT","volume":"18","year":"2023","unstructured":"Fill Hans-Georg, Peter Fettke, and Juluis K\u00f6pke. 2023. Conceptual Modeling and Large Language Models: Impressions From First Experiments With ChatGPT. Enterprise Modelling and Information Systems Architectures 18, 3 (2023), 1--15.","journal-title":"Enterprise Modelling and Information Systems Architectures"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2004.172"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Z. Hu et al. 2023. Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System. arXiv preprint arXiv:2306.09821 (2023).","DOI":"10.1145\/3583780.3615220"},{"key":"e_1_3_2_1_24_1","volume-title":"International Conference on Computers for Handicapped Persons. Springer, 77--84","author":"Karim S.","unstructured":"S. Karim and A. Tjoa. 2006. Towards the use of ontologies for improving user interaction for people with special needs. In International Conference on Computers for Handicapped Persons. Springer, 77--84."},{"key":"e_1_3_2_1_25_1","volume-title":"Advanced Information Systems Engineering: 8th International Conference, CAiSE'96 Heraklion","author":"Kelly S.","year":"1996","unstructured":"S. Kelly, K. Lyytinen, and M. Rossi. 1996. Metaedit+ a fully configurable multi-user and multi-tool case and came environment. In Advanced Information Systems Engineering: 8th International Conference, CAiSE'96 Heraklion, Crete, Greece, May 20-24, 1996 Proceedings 8. Springer, 1--21."},{"key":"e_1_3_2_1_26_1","unstructured":"T. Khot et al. 2022. Decomposed prompting: A modular approach for solving complex tasks. arXiv preprint arXiv:2210.02406 (2022)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"D. S. Kolovos et al. 2010. Taming EMF and GMF using model transformation. In Model Driven Engineering Languages and Systems. Springer 211--225.","DOI":"10.1007\/978-3-642-16145-2_15"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2015.11.001"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-021-00888-9"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-006-0017-9"},{"key":"e_1_3_2_1_31_1","unstructured":"S. K. Lahiri et al. 2022. Interactive code generation via test-driven user-intent formalization. arXiv preprint arXiv:2208.05950 (2022)."},{"key":"e_1_3_2_1_32_1","volume-title":"Rlaif: Scaling reinforcement learning from human feedback with ai feedback. arXiv preprint arXiv:2309.00267","author":"Lee H.","year":"2023","unstructured":"H. Lee et al. 2023. Rlaif: Scaling reinforcement learning from human feedback with ai feedback. arXiv preprint arXiv:2309.00267 (2023)."},{"key":"e_1_3_2_1_33_1","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","volume":"33","author":"Lewis P.","year":"2020","unstructured":"P. Lewis et al. 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems 33 (2020), 9459--9474.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_34_1","unstructured":"B. Li et al. 2023. Eliciting human preferences with language models. arXiv preprint arXiv:2310.11589 (2023)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"L. Luque et al. 2014. Can we work together? on the inclusion of blind people in uml model-based tasks. In Inclusive Designing: Joining Usability Accessibility and Inclusion. Springer 223--233.","DOI":"10.1007\/978-3-319-05095-9_20"},{"key":"e_1_3_2_1_36_1","unstructured":"G. Marcus E. Davis and S. Aaronson. 2022. A very preliminary analysis of DALL-E 2. arXiv preprint arXiv:2204.13807 (2022)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2875869"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"O. Metatla N. Bryan-Kinns and T. Stockman. 2008. Constructing relational diagrams in audio: the multiple perspective hierarchical approach. In Computers and accessibility. 97--104.","DOI":"10.1145\/1414471.1414491"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2009.67"},{"key":"e_1_3_2_1_40_1","unstructured":"F. Mu et al. 2023. ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification. arXiv preprint arXiv:2310.10996 (2023)."},{"key":"e_1_3_2_1_41_1","volume-title":"OOPSLA Workshop on Best Practices for Model-Driven Development.","author":"Muller P.","unstructured":"P. Muller, P. Studer, and J. J\u00e9z\u00e9quel. 2004. Model-driven generative approach for concrete syntax composition. In OOPSLA Workshop on Best Practices for Model-Driven Development."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1006\/jvlc.1993.1002"},{"key":"e_1_3_2_1_43_1","unstructured":"B. Nastov and F. Pfister. 2014. Experimentation of a Graphical Concrete Syntax Generator for Domain Specific Modeling Languages.. In INFORSID. 197--213."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"A. Pescador and J. de Lara. 2016. DSL-maps: from requirements to design of domain-specific languages. In Automated Software Engineering. 438--443.","DOI":"10.1145\/2970276.2970328"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"A. Rahimi et al. 2023. Towards Generating Structurally Realistic Models by Generative Adversarial Networks. In Model Driven Engineering Languages and Systems Companion. IEEE 597--604.","DOI":"10.1109\/MODELS-C59198.2023.00098"},{"key":"e_1_3_2_1_46_1","volume-title":"Workshop on OCL and Textual Modeling.","author":"Rajaei Z.","year":"2021","unstructured":"Z. Rajaei et al. 2021. A DSL for Encoding Models for Graph-Learning Processes. In Workshop on OCL and Textual Modeling."},{"key":"e_1_3_2_1_47_1","volume-title":"International conference on machine learning. PMLR, 8821--8831","author":"Ramesh A.","year":"2021","unstructured":"A. Ramesh et al. 2021. Zero-shot text-to-image generation. In International conference on machine learning. PMLR, 8821--8831."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-009-0122-7"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.3390\/fi15060192"},{"key":"e_1_3_2_1_50_1","volume-title":"Design: GPT-4 empowers Agile Model Driven Development. Report 2310.04304. arXiv.","author":"Sadik A.","year":"2023","unstructured":"A. Sadik, S. Brulin, and M. Olhofer. 2023. Coding by Design: GPT-4 empowers Agile Model Driven Development. Report 2310.04304. arXiv."},{"key":"e_1_3_2_1_51_1","volume-title":"International Conference on Conceptual Modeling. Springer, 65--83","author":"Sario\u011flu A.","unstructured":"A. Sario\u011flu, H. Metin, and D. Bork. 2023. How inclusive is conceptual modeling? A systematic review of literature and tools for disability-aware conceptual modeling. In International Conference on Conceptual Modeling. Springer, 65--83."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"T. Schick and H. Sch\u00fctze. 2021. Few-Shot Text Generation with Natural Language Instructions. In Empirical Methods in Natural Language Processing. ACL 390--402.","DOI":"10.18653\/v1\/2021.emnlp-main.32"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"O. B. Sghaier and H. Sahraoui. 2024. Improving the Learning of Code Review Successive Tasks with Cross-Task Knowledge Distillation. Report 2402.02063. arXiv.","DOI":"10.1145\/3643775"},{"key":"e_1_3_2_1_54_1","volume-title":"Sensecape: Enabling multilevel exploration and sensemaking with large language models. In User Interface Software and Technology. 1--18.","author":"Suh S.","year":"2023","unstructured":"S. Suh et al. 2023. Sensecape: Enabling multilevel exploration and sensemaking with large language models. In User Interface Software and Technology. 1--18."},{"key":"e_1_3_2_1_55_1","volume-title":"Model Driven Engineering Languages and Systems","volume":"1115","author":"Syriani E.","year":"2013","unstructured":"E. Syriani et al. 2013. AToMPM: A web-based modeling environment. In Model Driven Engineering Languages and Systems, Vol. 1115. CEUR-WS.org, 21--25."},{"key":"e_1_3_2_1_56_1","unstructured":"C. Tinnes et al. 2023. Towards Automatic Support of Software Model Evolution with Large Language~Models. Report 2312.12404. arXiv."},{"key":"e_1_3_2_1_57_1","volume-title":"Working Conference on Software Architecture. 45--54","author":"Van Gurp J.","unstructured":"J. Van Gurp, J. Bosch, and M. Svahnberg. 2001. On the notion of variability in software product lines. In Working Conference on Software Architecture. 45--54."},{"key":"e_1_3_2_1_58_1","volume-title":"Concrete Syntax: A Multi-Paradigm Modelling Approach. In Software Language Engineering. ACM, 182--193.","author":"Van Tendeloo Y.","year":"2017","unstructured":"Y. Van Tendeloo et al. 2017. Concrete Syntax: A Multi-Paradigm Modelling Approach. In Software Language Engineering. ACM, 182--193."},{"key":"e_1_3_2_1_59_1","volume-title":"Sirius: A rapid development of DSM graphical editor","author":"Viyovi\u0107 V.","year":"2014","unstructured":"V. Viyovi\u0107, M. Maksimovi\u0107, and B. Perisi\u0107. 2014. Sirius: A rapid development of DSM graphical editor. In Intelligent Engineering Systems. IEEE, 233--238."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3386252","article-title":"Generalizing from a few examples: A survey on few-shot learning","volume":"53","author":"Wang Y.","year":"2020","unstructured":"Y. Wang et al. 2020. Generalizing from a few examples: A survey on few-shot learning. Comput. Surveys 53, 3 (2020), 1--34.","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_1_61_1","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei J.","year":"2022","unstructured":"J. Wei et al. 2022. Chain-of-thought prompting elicits reasoning in large language models. Advances in Neural Information Processing Systems 35 (2022), 24824--24837.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10270-022-00975-5"},{"key":"e_1_3_2_1_63_1","volume-title":"Laws of Seeing","author":"Wolfgang M.","unstructured":"M. Wolfgang. 2006. Laws of Seeing. MIT Press."},{"key":"e_1_3_2_1_64_1","volume-title":"Model-Driven Engineering Languages and Systems","author":"Wouters L.","unstructured":"L. Wouters. 2013. Towards the notation-driven development of DSMLs. In Model-Driven Engineering Languages and Systems, Vol. 16. Springer, 522--537."},{"key":"e_1_3_2_1_65_1","volume-title":"Model Driven Engineering Languages and Systems Companion Proceedings. 396--403","author":"Yang S.","unstructured":"S. Yang and H. Sahraoui. 2022. Towards automatically extracting UML class diagrams from natural language specifications. In Model Driven Engineering Languages and Systems Companion Proceedings. 396--403."},{"key":"e_1_3_2_1_66_1","first-page":"10792","article-title":"Instruction Tuning for Large Language Models: A Survey","volume":"2308","author":"Zhang S.","year":"2023","unstructured":"S. Zhang et al. 2023. Instruction Tuning for Large Language Models: A Survey. Report 2308.10792. arXiv.","journal-title":"Report"}],"event":{"name":"MODELS '24: ACM\/IEEE 27th International Conference on Model Driven Engineering Languages and Systems","location":"Linz Austria","acronym":"MODELS '24","sponsor":["Johannes Kepler University, Linz, Austria","SIGSOFT ACM Special Interest Group on Software Engineering","IEEE CS"]},"container-title":["Proceedings of the ACM\/IEEE 27th International Conference on Model Driven Engineering Languages and Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640310.3674085","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3640310.3674085","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T23:52:47Z","timestamp":1755906767000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640310.3674085"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,22]]},"references-count":66,"alternative-id":["10.1145\/3640310.3674085","10.1145\/3640310"],"URL":"https:\/\/doi.org\/10.1145\/3640310.3674085","relation":{},"subject":[],"published":{"date-parts":[[2024,9,22]]},"assertion":[{"value":"2024-09-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}