Can we use LLM to quickly generate proper UML models from hand drawn model sketches? We set out to answer this question by comparing four different LLMs with vision capabilities
Access-control is a key element to manage security in any user interface. This is the first attempt to extend conversational user interfaces with access-control capabilities.
We tried to become rich by creating a model-driven chatbot solution. See what happened next.
Easily design and deploy community bots to help you manage your open source projects
Low-modeling platforms accelerate the modeling of a software system by dramatically reducing the amount of hand-modeling required
Curated collections of models are essential for the success of Machine Learning (ML) and Data Analytics in Model-Driven Engineering (MDE). However, there is still a lack of curated datasets of software models. We believe that there are several reasons for this,...
While research in Business Process Modeling has focused on events and processes, neglecting objects, research in Conceptual Modeling for Information Systems engineering has focused on objects, neglecting events. OEM reconciles both perspectives, giving equal weight to objects and events.
Uncertainty and inconsistency are inherent aspects of the development of any complex system. In practice, both must be tolerated to some extent so as not to inhibit engineers in their work, especially during the early stages of development.
Simplify the creation of configuration files for your software deployments with our new graphical environment able to generate docker compose files for you
We propose a DSL for prompt engineering to define platform-independent prompts that can later be adapted to provide good quality outputs in any target AI system
Large Language Models (LLMs) are being quickly integrated in a myriad of software applications. This may introduce a number of biases, such as gender, age or ethnicity, in the behavior of such applications. To face this challenge, we explore the automatic generation of tests to assess the potential biases of an LLM.