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Discussion on: "You Got This Error Last Week" — Building an AI That Remembers Your Past Errors

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motedb profile image
mote

One edge case worth considering: hash collisions in error fingerprinting. If two distinct errors normalize to the same signature (which can happen with complex stack traces that differ only inlining depth), your cache returns a misleading result. You mark it resolved once and the wrong diagnosis gets cached forever.

Your current normalization strips timestamps, PIDs, and line numbers. But object addresses, memory allocation patterns, and dynamic dispatch inlining are also common sources of false equivalence. The risk is low for a desktop helper with moderate traffic, but under high diversity of error inputs, you'll eventually get a collision that silently poisons the cache.

A practical fix: store the raw normalized text alongside the hash, and verify match on retrieval before returning from cache. Bloom filter as a pre-check is also cheap — if the Bloom filter says "never seen this", skip the lookup entirely.

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hiyoyok profile image
hiyoyo

Fair point on hash collisions — though for a local desktop helper with limited error diversity, the practical risk is low. Storing the normalized text alongside the hash for verification is a clean idea I'll keep in mind for future iterations. Thanks!