FA-12896 / Numerical aggregation / Open access
Clipped contribution sum: Outliers are dropped instead of contributing their clipped endpoint. · case 01
The reduction disagrees with its explicit aggregation oracle.
ROOT CAUSE
Outliers are dropped instead of contributing their clipped endpoint.
VERIFIED REPAIR
Preserve the clipped contribution sum contract at the identified reduction decision.
Unsuccessful approach: Only high outliers are clipped; low outliers are still dropped.
Case contract
For lo<=hi, clip each integer contribution into [lo,hi], then sum. Empty is zero.
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(xs, lo, hi):
return sum(x for x in xs if lo<=x<=hi)
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([-9, 2, 8], 0, 5)), 7)
check('regression 2', solve(*([], 1, 3)), 0)
check('regression 3', solve(*([1, 2, 3], 0, 5)), 6)
check('regression 4', solve(*([-4, -2], -3, -1)), -5)
check('regression 5', solve(*([0, 0, 9], 2, 4)), 8)
check("variable cap", solve([0,N,N*4],1,N+1),2*N+2)
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 |
|---|---|---|---|
| regression 1 | 2 | 7 | Failed |
| regression 2 | 0 | 0 | Passed |
| regression 3 | 6 | 6 | Passed |
| regression 4 | -2 | -5 | Failed |
| regression 5 | 0 | 8 | Failed |
| variable cap | 1 | 4 | Failed |
SHA-256 / 73c634a9d9a7181f2f8a4331b3a2c060a44d2b1b3dcb82253c45200b6bbee356
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(xs, lo, hi):
return sum(min(hi,x) for x in xs if x>=lo)
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([-9, 2, 8], 0, 5)), 7)
check('regression 2', solve(*([], 1, 3)), 0)
check('regression 3', solve(*([1, 2, 3], 0, 5)), 6)
check('regression 4', solve(*([-4, -2], -3, -1)), -5)
check('regression 5', solve(*([0, 0, 9], 2, 4)), 8)
check("variable cap", solve([0,N,N*4],1,N+1),2*N+2)
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 |
|---|---|---|---|
| regression 1 | 7 | 7 | Passed |
| regression 2 | 0 | 0 | Passed |
| regression 3 | 6 | 6 | Passed |
| regression 4 | -2 | -5 | Failed |
| regression 5 | 4 | 8 | Failed |
| variable cap | 3 | 4 | Failed |
SHA-256 / 2aa7e74fb3cd4ac87c877adc4817ef9924c37a07f272bea3b94362ba58244ff8
3 / The verified repair
Exit 0"""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(xs, lo, hi):
return sum(min(hi,max(lo,x)) for x in xs)
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([-9, 2, 8], 0, 5)), 7)
check('regression 2', solve(*([], 1, 3)), 0)
check('regression 3', solve(*([1, 2, 3], 0, 5)), 6)
check('regression 4', solve(*([-4, -2], -3, -1)), -5)
check('regression 5', solve(*([0, 0, 9], 2, 4)), 8)
check("variable cap", solve([0,N,N*4],1,N+1),2*N+2)
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 |
|---|---|---|---|
| regression 1 | 7 | 7 | Passed |
| regression 2 | 0 | 0 | Passed |
| regression 3 | 6 | 6 | Passed |
| regression 4 | -5 | -5 | Passed |
| regression 5 | 8 | 8 | Passed |
| variable cap | 4 | 4 | Passed |
SHA-256 / 292d2346600b360db4ccacda4326c8fc92cbbdeeb13fc7443e3492b695c3e822
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 2026-09-29T14:39:01.315374+00:00.
Case digest / 98182d5194fe70d9821add73eff2d90b97cbb9ff8f94a5e5c4db14542e526060