Engineer Uses Claude AI to Identify JNI Memory Leak via Core Dump Analysis

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A Lead QA Engineer used Anthropic's Claude Code AI tool to diagnose a persistent native memory leak in a high-throughput Java-C system connected via a JNI bridge. Standard diagnostic approaches failed: Valgrind caused the server to stall under load, and intrusive runtime monitoring by Claude itself crashed the environment. The team pivoted to an interval-based differential core dump strategy, using GDB to capture non-destructive memory snapshots every 30 minutes without halting the application. Claude analyzed the memory deltas across snapshots and identified a specific native C cache structure whose object count grew indefinitely without being released. The analysis pointed to a race condition in the production codebase as the root cause of the linear RSS growth observed in Grafana telemetry.

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