Data-driven inference of fault tree models exploiting symmetry and modularization
Lisandro A. Jiménez-Roa, Matthias Volk, Mariëlle I. A. Stoelinga · Zenodo (CERN European Organization for Nuclear Research) · 2021
This dataset contains (i) the Python source code of the SymLearn toolchain and the improved implementation of the FT-MOEA algorithm (used to infer Fault Tree models in a data-driven manner); (ii) the failure dataset for five case studies. The latter used as input to our implementation; and (iii) the results obtained from our toolchain for the case studies.