
Developed the Probability Distributions core library for the CSE498-Spring2025 repository, implementing a Distribution class with support for Binomial and Uniform distributions in C++. Focused on robust algorithm implementation and object-oriented design, the work included pre-calculation techniques to accelerate graph generation and comprehensive unit testing to ensure reliability. Enhanced error handling with clear exception logic and improved code quality through documentation, clang formatting, and targeted refactoring. Further contributions included clarifying the semantics of the noChance variable in Distribution.hpp, strengthening code readability and maintainability. Emphasized maintainable software engineering practices, supporting future contributors through detailed documentation and clear code structure.
March 2025 monthly summary for the CSE498/CSE498-Spring2025 repository: key documentation effort completed with a clarifying update to the noChance semantics in Distribution.hpp. The change improves readability and maintainability without altering behavior, supporting clearer code comprehension and future enhancements.
March 2025 monthly summary for the CSE498/CSE498-Spring2025 repository: key documentation effort completed with a clarifying update to the noChance semantics in Distribution.hpp. The change improves readability and maintainability without altering behavior, supporting clearer code comprehension and future enhancements.
February 2025 monthly summary for the CSE498 project: Implemented the Probability Distributions core library (Distribution class) with support for Binomial and Uniform distributions, added pre-calculation to speed graph generation, and built comprehensive test coverage. Performed targeted refactors to improve robustness and maintainability, enhanced error handling with clearer Distribution exceptions, and applied code-quality improvements following reviews (clang formatting, documentation and comments). These changes deliver business value by enabling faster and more reliable probabilistic modeling and graph rendering for teaching/analysis workflows.
February 2025 monthly summary for the CSE498 project: Implemented the Probability Distributions core library (Distribution class) with support for Binomial and Uniform distributions, added pre-calculation to speed graph generation, and built comprehensive test coverage. Performed targeted refactors to improve robustness and maintainability, enhanced error handling with clearer Distribution exceptions, and applied code-quality improvements following reviews (clang formatting, documentation and comments). These changes deliver business value by enabling faster and more reliable probabilistic modeling and graph rendering for teaching/analysis workflows.

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