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Refinery

An efficient graph solver for generating well-formed models

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Features

Diverse graph generation

Refinery provides a framework for the automated generation of graphs.

Model with uncertainty

Partial modeling allows us to explicitly represent unknown or uncertain knowledge in our models. The Refinery framework enables us to explore design alternatives systematically.

Formal logic reasoning

Refinery combines the mathematical precision of formal logic structures with the expressiveness of graph-based models. Underlying solver algorithms ensure formal correctness and completeness of generation processes.

Advanced web-based editor

Designers are supported with state-of-the-art web-based editors with advanced IDE features and visualization techniques. The framework can be applied as a simple command-line interface program or deployed on the cloud.

Powerful graph algorithms

Refinery is equipped with powerful algorithms such as incremental query evaluation, efficient graph isomorphism checking, and version-controlled data structures to solve various modeling and graph processing problems.

Check out the intro video

Explore use-cases

Scenario generation for testing autonomous vechicles

Conformance checking of modeling toolchains

Synthesize distributed communication networks

Execution time analysis for data-driven critical systems

Generative architectures with assured resilience

Video game map generator with model-based techniques

Related publications

Tool demonstration

  • K. Marussy, A. Ficsor, O. Semeráth, D. Varró: “Refinery: Graph Solver as a Service” ICSE 2024 Demonstrations [doi] [pdf] [video]

Partial model specification language

  • K. Marussy, O. Semeráth, A. Babikian, D. Varró: A Specification Language for Consistent Model Generation based on Partial Models. J. Object Technol. 19(3): 3:1-22 (2020) [doi] [pdf] [video]

Diverse and realistic graph generation

  • O. Semeráth, R. Farkas, G. Bergmann, D. Varró: Diversity of graph models and graph generators in mutation testing. Int. J. Softw. Tools Technol. Transf. 22(1): 57-78 (2020) [doi] [pdf]
  • O. Semeráth, A. Babikian, B. Chen, C. Li, K. Marussy, G. Szárnyas, D. Varró: Automated generation of consistent, diverse and structurally realistic graph models. Softw. Syst. Model. 20(5): 1713-1734 (2021) [doi] [pdf]

Consistent graph generation techniques

  • O. Semeráth, A. Nagy, D. Varró: “A graph solver for the automated generation of consistent domain-specific models.” ICSE 2018: 969-980 [doi] [pdf]
  • K. Marussy, O. Semeráth, D. Varró: Automated Generation of Consistent Graph Models With Multiplicity Reasoning. IEEE Trans. Softw. Eng. 48(5): 1610-1629 (2022) [doi] [pdf]
  • A. Babikian, O. Semeráth, A. Li, K. Marussy, D. Varró: Automated generation of consistent models using qualitative abstractions and exploration strategies. Softw. Syst. Model. 21(5): 1763-1787 (2022) [doi] [pdf]

Correctness proofs

  • D. Varró, O. Semeráth, G. Szárnyas, Á. Horváth: “Towards the Automated Generation of Consistent, Diverse, Scalable and Realistic Graph Models.” Graph Transformation, Specifications, and Nets 2018: 285-312 [doi] [pdf]