FA-100316 / Dataset deduplication grouping / Open access

Dataset deduplication: signature selects maximum hash per band · case 01

signature selects maximum hash per band.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The sketch reducer maximizes components, selecting unrelated hash values.

THE FAILURE

The sketch reducer maximizes components, selecting unrelated hash values.

Unsuccessful approach: Taking one global minimum and repeating it loses the per-component minima.

Case contract

Return the componentwise minimum of nonempty equal-width integer signatures; empty input returns [].

Why this case matters

This deterministic toy operation makes one dataset equivalence or representative rule explicit.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(signatures):
    return [max(col) for col in zip(*signatures)] if signatures else []
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('component minima',solve([[N+2,N],[N,N+3]]),[N,N])
check('single signature',solve([[1,2,3]]),[1,2,3])
check('empty signatures',solve([]),[])
check('three rows',solve([[3,8],[2,7],[4,1]]),[2,1])
check('identical',solve([[N,N],[N,N]]),[N,N])
check('mixed minima',solve([[1,9,4],[5,2,3]]),[1,2,3])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
component minima	`[3, 4]`	`[1, 1]`	Failed
single signature	`[1, 2, 3]`	`[1, 2, 3]`	Passed
empty signatures	`[]`	`[]`	Passed
three rows	`[4, 8]`	`[2, 1]`	Failed
identical	`[1, 1]`	`[1, 1]`	Passed
mixed minima	`[5, 9, 4]`	`[1, 2, 3]`	Failed

SHA-256 / 8ea29ee387352e4401339031e5a267535082e07f7940d6057e0c0a58db8aca47

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(signatures):
    m=min((min(row) for row in signatures),default=0); return [m]*len(signatures[0]) if signatures else []
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('component minima',solve([[N+2,N],[N,N+3]]),[N,N])
check('single signature',solve([[1,2,3]]),[1,2,3])
check('empty signatures',solve([]),[])
check('three rows',solve([[3,8],[2,7],[4,1]]),[2,1])
check('identical',solve([[N,N],[N,N]]),[N,N])
check('mixed minima',solve([[1,9,4],[5,2,3]]),[1,2,3])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
component minima	`[1, 1]`	`[1, 1]`	Passed
single signature	`[1, 1, 1]`	`[1, 2, 3]`	Failed
empty signatures	`[]`	`[]`	Passed
three rows	`[1, 1]`	`[2, 1]`	Failed
identical	`[1, 1]`	`[1, 1]`	Passed
mixed minima	`[1, 1, 1]`	`[1, 2, 3]`	Failed

SHA-256 / 8582b793fb3b14e59ba660da7aba5f861e892daee82e2dba1feafd4a9899ae5e

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 6 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

Member access is invitation-based. Sign in with your invited account to inspect the repair.

Verification & scope

Inputs are small in-memory fixtures with the stated contract; results do not claim production deduplication quality. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-30T16:48:34.044850+00:00.

Case digest / 7727a93b8b0d1c59864190b1b3974b7e9c3b75b39ec9af2797a0e903b8149f03