
Worked on the Samsung/TizenRT repository to enhance the stability of math kernel tests by addressing a stack overflow issue in the test harness. Using C programming and a strong understanding of embedded systems and kernel development, the developer identified that local arrays were incorrectly sized, leading to oversized stack frames and kernel crashes, especially at lower optimization levels. By resizing the ret_val array to match input dimensions and aligning loop bounds with actual usage, the patch improved test reliability and reduced flaky CI runs. This work increased confidence in kernel behavior, streamlined release cycles, and made future test maintenance more manageable.
May 2026, Samsung/TizenRT: Stabilized the math kernel test path by fixing stack overflow in tests (jn/jnf) through correct resizing of the local ret_val array to match in_val dimensions. Root cause was ret_val sized by sol_val, causing oversized frames at -O0; the patch aligns loop bounds with actual usage, preventing kernel crashes across optimization levels (-O0 to -Os). This work improves test reliability, reduces flaky CI runs, and strengthens kernel_tc stability. Technologies demonstrated include C memory management, test harness hardening, and understanding of compiler optimizations and stack usage. Business value: higher confidence in math kernel behavior, faster release cycles, and reduced maintenance burden.
May 2026, Samsung/TizenRT: Stabilized the math kernel test path by fixing stack overflow in tests (jn/jnf) through correct resizing of the local ret_val array to match in_val dimensions. Root cause was ret_val sized by sol_val, causing oversized frames at -O0; the patch aligns loop bounds with actual usage, preventing kernel crashes across optimization levels (-O0 to -Os). This work improves test reliability, reduces flaky CI runs, and strengthens kernel_tc stability. Technologies demonstrated include C memory management, test harness hardening, and understanding of compiler optimizations and stack usage. Business value: higher confidence in math kernel behavior, faster release cycles, and reduced maintenance burden.

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