Worked on enhancing the reliability of function argument detection within the angr/angr repository’s calling convention analysis. Focused on resolving issues with overly aggressive argument identification, the work involved refining static analysis techniques and expanding regression test coverage to ensure accuracy across diverse binary contexts. Leveraging skills in binary analysis, reverse engineering, and Python, the developer adopted a test-driven approach to validate improvements and reduce edge-case failures. By addressing a critical bug and introducing comprehensive tests, the changes strengthened the robustness of function argument identification, supporting downstream analysis pipelines and contributing to higher code quality within the static analysis framework.