Most experts agree that large language models (LLMs), such as those used by Copilot and ChatGPT, are expected to revolutionize the way in which software is developed. Many papers are currently devoted to analyzing the potential advantages and limitations of these generative AI models for writing code. However, the analysis of the current state of LLMs with respect to software modeling has received little attention. In this paper, we investigate the current capabilities of ChatGPT to perform modeling tasks and to assist modelers, while also trying to identify its main shortcomings. Our findings show that, in contrast to code generation, the performance of the current version of ChatGPT for software modeling is limited, with various syntactic and semantic deficiencies, lack of consistency in responses and scalability issues. We also outline our views on how we perceive the role that LLMs can play in the software modeling discipline in the short term, and how the modeling community can help to improve the current capabilities of ChatGPT and the coming LLMs for software modeling.

Current Web service choreography proposals, such as BPEL4WS, BPSS, WSFL, WSCDL or WSCI, provide notations for describing the message flows in Web service collaborations. However, such proposals remain at the descriptive level, without providing any kind of reasoning mechanisms or tool support for checking the compatibility of Web services based on the proposed notations. In this paper we present the formalization of one of these Web service choreography proposals (WSCI), and discuss the benefits that can be obtained by such formalization. In particular, we show how to check whether two or more Web services are compatible to interoperate or not, and, if not, whether the specification of adaptors that mediate between them can be automatically generated ---hence enabling the communication of (a priori) incompatible Web services.

Modeling languages play a cornerstone role in model-driven software development for representing models and metamodels. Modeling languages are usually defined in terms of their abstract and concrete syntax. This allows the rapid development of languages and some associated tools (e.g. editors), but does not allow the representation of their behavioral semantics, something especially important in certain industrial environments in which simulation and verification are critical issues. In this paper we explore the use of Maude as a formal notation for describing models, metamodels, and their dynamic behavior, making models amenable to formal analysis, reasoning, and simulation.