PyMBD: A Library of MBD Algorithms and a Light-weight Evaluation Platform
نویسنده
چکیده
Facing a diagnostic challenge, the decision about the algorithmic variant to adopt for a certain project is a challenging one. With PyMBD, we provide an easily accessible Python library, offering our implementations of several established model-based diagnosis (MBD) algorithms that a user can experiment with. Via the integrated experimentation features, a user can also delve into assessing the effects of her algorithmic changes and optimizations. That is, algorithm authors can run evaluations and generate comparison graphs via accessing simple interfaces to algorithms and backends such as SAT solvers. C-based algorithms (or algorithm parts) can be interfaced via the Boost.Python library.
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