review: Suppress validated false positives from LKML reviews#35
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Require the strong validation stage to independently adjudicate every baseline finding before LKML rendering. Each finding must receive an exact, ordered KEEP or DROP decision with structured proof backed by repository inspection. Reject incomplete or mismatched adjudications and preserve the baseline on validation or tool-verification failure. Apply DROP only when the validator copies the complete finding and conclusively proves it's a false positive. Keep deterministic upstream-fix findings unconditionally. This improves the signal-to-noise ratio of LKML-style reviews by suppressing findings that have been conclusively proven to be false positives while reporting all validated findings. Signed-off-by: Andrea Righi <arighi@nvidia.com>
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Require the strong validation stage to independently adjudicate every baseline finding before LKML rendering. Each finding must receive an exact, ordered KEEP or DROP decision with structured proof backed by repository inspection.
Reject incomplete or mismatched adjudications and preserve the baseline on validation or tool-verification failure. Apply DROP only when the validator copies the complete finding and conclusively proves it's a false positive. Keep deterministic upstream-fix findings unconditionally.
This improves the signal-to-noise ratio of LKML-style reviews by suppressing findings that have been conclusively proven to be false positives while reporting all validated findings.