International audience

International audience

SysML models are widely used for designing and analyzing complex systems. Model-based design methods often require successive modifications of the models, whether for incrementally refining the design (e.g., in agile development methods) or for testing different design options. Such modifications, or mutations, are also used in mutation-based testing approaches. However, the definition of mutation operators can be a complex issue, and applying them to models is sometimes performed by hand: this is time consuming and error prone. This article addresses this issue thanks to the introduction of AMULET, the first mutation language for SysML. AMULET encompasses the modifications targeting SysML block and state-machine diagrams and is supported by a compiler the article presents. This compiler is integrated in TTool, an open-source SysML toolkit, enabling the full support of design methods including model design, mutation, and verification tasks in a unique toolkit. The article also introduces two case studies providing concrete examples of AMULET use for modeling vulnerabilities and cyber attacks and highlighting the benefits of AMULET for SysML mutations.

Graphical modeling languages, expected to simplify systems analysis and design, present a challenge in maintaining consistency across their varied views. Traditional rule-based methods for ensuring consistency in languages like UML often fall short in addressing complex semantic dimensions. Moreover, the integration of Large Language Models (LLMs) into Model Driven Engineering (MDE) introduces additional consistency challenges, as LLM's limited output contexts requires the integration of responses. This paper presents a new framework that automates the detection and correction of inconsistencies across different views, leveraging formally defined rules and incorporating OpenAI's GPT, as implemented in TTool. Focusing on the consistency between use case and block diagrams, the framework is evaluated through its application to three case studies, highlighting its potential to significantly enhance consistency management in graphical modeling.

International audience

International audience