Google Rewrites Critical C Dependencies to Rust Using AI and Differential Fuzzing
Google engineers have successfully rewritten critical C and C++ library dependencies into Rust using an automated pipeline powered by Gemini, differential fuzzing, and human expert validation. The automated feedback loop achieved bit-for-bit rendering parity across millions of assets while mitigating memory corruption vulnerabilities.
Why it matters
This approach demonstrates a scalable path forward for migrating massive, legacy codebases to memory-safe languages using generative AI and automated testing.
InfoQ Homepage News Google Rewrites Critical C Dependencies to Rust Using AI and Differential Fuzzing
Memory corruption bugs represent roughly 70 per cent of severe security vulnerabilities in mature C and C++ stacks. Rather than undertaking multi-year manual conversions or relying entirely on runtime bounds checking, software engineers Bastian Kersting and Max Hils executed a three-stage automated migration process designed around an autonomous feedback loop.
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