Contributed to the pymc-devs/pymc repository by implementing the inverse cumulative distribution function (ICDF) for the Kumaraswamy distribution, expanding the library’s statistical modeling capabilities. The work involved developing precision-based truncation for the cumulative distribution function to enhance numerical stability and adding consistency tests to verify the correctness of ICDF and logCDF outputs. Addressed issues in the test suite by removing brittle temporary tests, which stabilized continuous integration and improved maintainability. Collaborated closely with teammates to validate changes and ensure code quality. Utilized Python for development and testing, focusing on robust statistical computation and reliable automated test coverage throughout the process.