During August 2025, contributed to the tensorflow/tensorflow repository by developing a Memory Dump Readability Enhancement for large tuples within the XLA memory-dump tooling. This feature improved the analysis of buffer allocations by printing subshapes instead of full shapes, streamlining the debugging process for complex tuple structures. The work focused on C++ development and performance optimization, integrating formatting changes with minimal disruption to existing workflows. By enhancing the clarity of memory dumps, the update enabled faster triage of memory-related issues and supported maintainability for future development. No major bugs were addressed during this period, with efforts concentrated on feature delivery.