During the early modeling phase, model developers must manage a wide range of potential design alternatives that are frequently incomplete or inconsistent. However, existing modeling tools force developers to work with concrete models, making developers formulate possible design decisions outside the modeling editor and losing the available model validation or transformation support.
Partial modeling is a technique to support the explicit modeling of uncertainty in models, which needs mathematically precise reasoning tools to inform the user about the impact of each design decision on the range of valid models. Scalability challenges make traditional logic solvers ill-equipped to analyze partial graph models in industrial contexts.
More recently, the Refinery framework has been introduced to manage partial models and carry out analysis and graph generation using algorithms specifically tailored for large software and system models. In this tutorial, we present the partial modeling formalism and language offered by Refinery and showcase its analysis and graph generation capabilities for (1) querying and reasoning over models with incomplete information, (2) pinpointing validation errors and inconsistencies in information coming from multiple sources, and (3) concretizing partial models to obtain possible test cases or design candidates automatically. The tutorial leverages Refinery’s web-based partial modeling environment for an installation-free experience.
Refinery website: https://refinery.tools
Video demonstration of Refinery: https://youtu.be/Qy_3udNsWsM
Continuously deployed at: https://refinery.services/
Sun 22 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
16:00 - 17:30 | |||
16:00 90mTutorial | T9: Refinery: Logic-based Partial Modeling Tutorials Kristóf Marussy Budapest University of Technology and Economics, Oszkár Semeráth Budapest University of Technology and Economics, Attila Ficsor Budapest University of Technology and Economics, Daniel Varro Linköping University / McGill University | ||
Kristóf Marussy is a research fellow at the Department of Measurement and Information Systems at Budapest University of Technology and Economics. He was also a research assistant at the MTA Lendület Cyber-Physical Systems Research Group. His research interests include the modeling and analysis of extra-functional properties of cyber-physical systems, and the synthesis of reliable architectures. He participated in research visits to the University of L’Aquila and McGill University. He is the course coordinator of the Critical Systems Laboratory MSc course at Budapest University of Technology Enconomics, where he teaches students advanced logic-based and stochastic analysis techniques, including partial modeling, for ensuring the safety of critical systems. Previously, he has been involved as a teaching assistant in numerous courses at his host institute for over 6 years, which includes various labs and tutorials. He also delivered presentations at software engineering conferences, including two presentations at MODELS.