Expressing Confidence in Models and Model Transformation

Models need to represent the reality as accurately as possible. Nevertheless, complex systems are subject to uncertainty something difficult to express with plain UML. We propose a way to represent uncertainty on software models. Our uncertainty values can then be propagated through model transformations to evaluate the impact on other parts of the system.

Robust Hashing for Models

We present a novel robust hashing mechanism for models. Robust hashing algorithms (i.e. hashing algorithms that generate similar outputs from similar input data) are useful as a key building block in intellectual property protection, authenticity assessment and fast comparison and retrieval solutions


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