Dariya Mamayeva developed the LARX Generator for Cayley growth datasets within the Cayleypy repository, focusing on reproducible synthetic data generation for growth simulations in graph theory. She implemented the generator in Python, ensuring comprehensive test coverage to maintain reliability and prevent regressions. To streamline continuous integration workflows, Dariya updated the pyproject.toml configuration to ignore a specific linting rule, reducing unnecessary CI noise and improving stability. Her work addressed the need for robust, testable data generation tools in the Cayleypy library, demonstrating depth in both data generation and testing practices while contributing to smoother downstream use for other developers and researchers.