3.2 KiB
3.2 KiB
type:: REVIEWS tags:: year:: 2025 venue:: MODELS-WS full-title:: date-start:: 30-07-2025 - 14:58 date-submitted:: external-links:: status:: DONE deadline-submission:: file:: @LLM-assisted configuration of model-driven business process families parent:: todoist:: https://app.todoist.com/app/task/6-daniel-calegari-and-andrea-delgado-llm-assisted-configuration-of-model-driven-6cVfQ9jXM6pqQv9c
- LLM-assisted configuration of model-driven business process families
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- ### [[Highlights]]
- ### [[Comments]]
- The paper proposes an approach to integrate Large Language Models (LLMs) with a model-driven engineering (MDE) framework for managing business process families. The approach builds on the existing Business Process Family Manager (BPFM) tool and leverages LLMs to generate questionnaires that guide users through the configuration of process variants. The process is supported by metamodels, model-to-model transformations, and a questionnaire mechanism, aiming to improve the configuration of business process variants.
DETAILED COMMENTS: The paper is about an interesting problem. However, several aspects need clarification to make the contribution clearer and more convincing, as discussed below:
- First, the novelty of this work compared to reference [3] must be made explicit early in the paper. Much of the metamodel and underlying concepts are reused, and the added value of integrating LLMs should be better highlighted. Similarly, the BPFM tool appears central to the approach, but its last update dates back four years; this raises concerns about its current applicability and maintenance status, which should be discussed.
- The description of business process families is at the conceptual level and remains abstract. To help readers better grasp the approach, illustrative examples of process variants, variation points, and contexts should be introduced earlier in the paper. The same holds for the questionnaire mechanism: while the paper explains that questionnaires guide the configuration, concrete examples of questions should be given, otherwise it's hard to visualize their practical usage. Examples should also be added when discussing how questions relate to facts and dependencies, and when explaining the three parts of the prompt used for LLM generation.
- Regarding the LLM-assisted part, the zero-shot experiment is verbose and lacks concrete examples, making the results difficult to interpret.
- The evaluation mentions metrics based on semantic equivalence, but how this equivalence was assessed is unclear. Clarifying the methodology here is essential.
- The configurations produced by the approach are a crucial output, yet the paper does not sufficiently explain how these configurations are "consumed" in practice.
- Finally, details on the technological updates and how they improve over the original proposal [9] would make the paper convincing.
Overall, while the paper introduces an interesting integration of LLMs in the configuration of business process families, it requires additional illustrative examples and a more explicit discussion of the approach's novelty and the tool's applicability.