Why filtered data should be labeled, not deleted, in software systems

A software developer building a mileage-tracking app discovered a critical flaw months after shipping a GPS data filter: rejected readings were being permanently deleted, making it impossible to verify whether the filter was working correctly. The fix involved replacing hard deletions with labeled categories, so that implausible GPS points were marked and stored rather than discarded, with only physically impossible values still removed entirely. This approach allowed disputed expense claims to be resolved by showing drivers exactly which readings were excluded and why. Tunable thresholds became possible because engineers could replay real journeys and adjust filtering logic based on retained data. The developer argues this principle applies broadly to any system that rejects data — from fraud scoring to log pipelines — since deleting a record destroys the only evidence needed to audit the decision.