FAILURE MAP
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FA-13051 / Numerical aggregation / Open access

Histogram interval mass: Reversed query bounds are silently sorted into a nonempty query. · case 01

The reduction disagrees with its explicit aggregation oracle.

Verified by executionVariant 1 · 9 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Reversed query bounds are silently sorted into a nonempty query.

THE FAILURE

Reversed query bounds are silently sorted into a nonempty query.

Unsuccessful approach: Expanding the right edge confuses interval length with integer point counting.

Case contract

Bins [left,right,mass] have positive widths and nonnegative integer masses. Treat each bin as uniform density. Return exact mass in query [a,b] as a Fraction string; reversed/empty queries have zero mass.

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(bins, a, b):
    return str(sum((Fraction(m*max(0,min(r,max(a,b))-max(l,min(a,b))),r-l) for l,r,m in bins),Fraction(0)))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([[0, 4, 8], [4, 10, 3]], 2, 7)), '11/2')
check('regression 2', solve(*([[0, 4, 8]], 1, 2)), '2')
check('regression 3', solve(*([[0, 4, 8]], -3, 8)), '8')
check('regression 4', solve(*([[0, 4, 8]], 4, 9)), '0')
check('regression 5', solve(*([[0, 4, 8]], 7, 9)), '0')
check('regression 6', solve(*([], 0, 1)), '0')
check('regression 7', solve(*([[0, 4, 8]], 3, 1)), '0')
check('regression 8', solve(*([[2, 7, 10], [10, 12, 8]], 0, 11)), '14')
check("variable density mass",solve([[0,N+2,2*(N+2)]],1,N+1),str(2*N))
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 111/211/2Passed
regression 222Passed
regression 388Passed
regression 400Passed
regression 500Passed
regression 600Passed
regression 740Failed
regression 81414Passed
variable density mass22Passed

SHA-256 / 770846cc79107a80622a37fe431847994439f401c61da88762253b236153a2bd

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(bins, a, b):
    return str(sum((Fraction(m*max(0,min(r,b+1)-max(l,a)),r-l) for l,r,m in bins),Fraction(0))) if a<=b else "0"
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('regression 1', solve(*([[0, 4, 8], [4, 10, 3]], 2, 7)), '11/2')
check('regression 2', solve(*([[0, 4, 8]], 1, 2)), '2')
check('regression 3', solve(*([[0, 4, 8]], -3, 8)), '8')
check('regression 4', solve(*([[0, 4, 8]], 4, 9)), '0')
check('regression 5', solve(*([[0, 4, 8]], 7, 9)), '0')
check('regression 6', solve(*([], 0, 1)), '0')
check('regression 7', solve(*([[0, 4, 8]], 3, 1)), '0')
check('regression 8', solve(*([[2, 7, 10], [10, 12, 8]], 0, 11)), '14')
check("variable density mass",solve([[0,N+2,2*(N+2)]],1,N+1),str(2*N))
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 1611/2Failed
regression 242Failed
regression 388Passed
regression 400Passed
regression 500Passed
regression 600Passed
regression 700Passed
regression 81814Failed
variable density mass42Failed

SHA-256 / d3cf1e3d5d126dfac8a1d3a4544e28352ed7183502a65e7b427bbe187251e3e1

HELD IN THE MEMBER ARCHIVE

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

This mechanism has 9 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 2026-09-29T14:39:03.075051+00:00.

Case digest / f593816cfc627eb34cf78908984c407b31663ff9b0a8c993f62b7f8ed542ccda