FAILURE MAP
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FA-13301 / Numerical aggregation / Open access

Frequency symmetric trim mean: Trimming treats each compressed row as one observation. · case 01

The reduction disagrees with its explicit aggregation oracle.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Trimming treats each compressed row as one observation.

THE FAILURE

Trimming treats each compressed row as one observation.

Unsuccessful approach: Unique support still ignores frequency when locating trim boundaries.

Case contract

Expand nonnegative integer frequencies. Remove exactly k lowest and k highest observations by multiplicity. Return the exact mean as a Fraction string, or None when no observations survive.

Why this case matters

Exact bounded examples isolate a reduction defect without floating-point or external-service effects.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
from collections import Counter, defaultdict
import math
import itertools
N = 1
observations = []
def solve(rows, k):
    xs=sorted(x for x,w in rows if w>0)
    if not xs or 2*k>=len(xs): return None
    return str(Fraction(sum(xs[k:len(xs)-k]),len(xs)-2*k))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([(9, 1), (1, 4), (5, 2)], 2)), '7/3')
check('regression 2', solve(*([(2, 4)], 1)), '2')
check('regression 3', solve(*([], 0)), None)
check('regression 4', solve(*([(1, 2), (4, 2)], 2)), None)
check('regression 5', solve(*([(0, 1), (10, 3), (-5, 2)], 1)), '15/4')
check('regression 6', solve(*([(3, 0), (8, 1)], 0)), '8')
check('regression 7', solve(*([(1, 1), (8, 4), (9, 1)], 1)), '8')
check("variable weighted trim",solve([(N,3),(N+6,2)],1),str(Fraction(3*N+6,3)))
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 fixtureActualExpectedOutcome
regression 1None7/3Failed
regression 2None2Failed
regression 3NoneNonePassed
regression 4NoneNonePassed
regression 5015/4Failed
regression 688Passed
regression 788Passed
variable weighted trimNone3Failed

SHA-256 / 9d803f4ce091defa3140db3e51fdb17a000a9bfb2d2b6605370646c223ba50da

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
from collections import Counter, defaultdict
import math
import itertools
N = 1
observations = []
def solve(rows, k):
    xs=sorted(set(x for x,w in rows if w>0))
    if not xs or 2*k>=len(xs): return None
    return str(Fraction(sum(xs[k:len(xs)-k]),len(xs)-2*k))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([(9, 1), (1, 4), (5, 2)], 2)), '7/3')
check('regression 2', solve(*([(2, 4)], 1)), '2')
check('regression 3', solve(*([], 0)), None)
check('regression 4', solve(*([(1, 2), (4, 2)], 2)), None)
check('regression 5', solve(*([(0, 1), (10, 3), (-5, 2)], 1)), '15/4')
check('regression 6', solve(*([(3, 0), (8, 1)], 0)), '8')
check('regression 7', solve(*([(1, 1), (8, 4), (9, 1)], 1)), '8')
check("variable weighted trim",solve([(N,3),(N+6,2)],1),str(Fraction(3*N+6,3)))
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 fixtureActualExpectedOutcome
regression 1None7/3Failed
regression 2None2Failed
regression 3NoneNonePassed
regression 4NoneNonePassed
regression 5015/4Failed
regression 688Passed
regression 788Passed
variable weighted trimNone3Failed

SHA-256 / 387bd89ba61464e3477b5de749f12959a9b50ff25ba0ada3e3b755a5d6f43462

HELD IN THE MEMBER ARCHIVE

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

This mechanism has 8 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.

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Verification & scope

Small offline integer/rational inputs only; no performance, statistical inference, or production-library conformance claim. 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 2026-09-29T14:39:06.052066+00:00.

Case digest / 47a66b6e8427322a5304192db1dd873f1bc69c7871ad7ce05c1c35921080b165