Worked on the SciCompMod/memilio repository, focusing on improving the reliability of stochastic SIRS simulations used in scientific computing workflows. Addressed a critical bug by correcting an undefined variable in the Python-based SDE SIRS example, ensuring that simulations execute properly and produce reproducible results for downstream analyses. The technical approach involved careful debugging and validation of the modeling path to prevent incorrect runs, with an emphasis on code quality and maintainability. Utilized Python programming and scientific computing skills to deliver a targeted fix, prioritizing stability and correctness over new feature development during this period to support research reproducibility.