
George Faraj developed a deterministic random number generator module for the CSE498/CSE498-Spring2025 repository, focusing on reproducibility and reliability in simulation workflows. He designed and implemented a C++ Random class with a seedable API, supporting uniform generation of doubles, integers, and probabilities across numeric types. George consolidated implementation into a modern header-only format using C++ and Makefile, improving maintainability and build integration. He established a robust testing infrastructure with unit tests and assertions for error handling, ensuring correctness across distributions and seed scenarios. His work delivered a reusable, stable randomness component, demonstrating depth in software design, build systems, and testing.

February 2025 monthly summary for CSE498-CSE498-Spring2025. Focused on delivering a robust Random module API and establishing testing infrastructure to ensure reliability of randomness utilities used in simulations and numerical experiments. Key work spanned API surface, header consolidation, and test/build workflow improvements.
February 2025 monthly summary for CSE498-CSE498-Spring2025. Focused on delivering a robust Random module API and establishing testing infrastructure to ensure reliability of randomness utilities used in simulations and numerical experiments. Key work spanned API surface, header consolidation, and test/build workflow improvements.
Month: 2025-01 — Delivered initial specifications for a Deterministic Random Number Generator (RNG) class to support reproducible simulations across multiple numeric types. This foundational work defines seeding for reproducibility and uniform generation for doubles, integers, and probability values, with error handling and cross-type usage considerations. No major bug fixes recorded this month.
Month: 2025-01 — Delivered initial specifications for a Deterministic Random Number Generator (RNG) class to support reproducible simulations across multiple numeric types. This foundational work defines seeding for reproducibility and uniform generation for doubles, integers, and probability values, with error handling and cross-type usage considerations. No major bug fixes recorded this month.
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