FA-14716 / Numerics / Open access
Forward difference newton basis: table depth · case 01
The exact forward difference newton basis result violates the stated contract at table depth.
ROOT CAUSE
The table depth step uses range(len(x)-1) instead of range(len(x)).
THE FAILURE
The table depth step uses range(len(x)-1) instead of range(len(x)).
Unsuccessful approach: The partial repair range(1,len(x)) still violates the table depth invariant.
Case contract
Input nonempty integer sequence f(0)..f(n); return binomial-basis coefficients Delta^k f(0).
Why this case matters
Exact discrete arithmetic with observable algorithmic state; no floating point approximation is used.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
import itertools
from fractions import Fraction
N = 1
observations = []
def solve(x):
row=x[:];out=[]
for _ in range(len(x)-1):
if not row:break
out.append(row[0])
row=[row[i+1]-row[i] for i in range(len(row)-1)]
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([0], [0]), ([1], [1]), ([-1, -1], [-1, 0]), ([-1, 0], [-1, 1]), ([-1, 1], [-1, 2]), ([0, -1], [0, -1])], [([0], [0]), ([-1, -1], [-1, 0]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([-1, 0, 1], [-1, 1, 0]), ([-1, 1, -1], [-1, 2, -4]), ([-1, 1, 0], [-1, 2, -3]), ([-1, 1, 1], [-1, 2, -2])], [([1], [1]), ([0, -1], [0, -1]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([1, 0, 0], [1, -1, 1]), ([1, 0, 1], [1, -1, 2]), ([1, 1, -1], [1, 0, -2]), ([1, 1, 0], [1, 0, -1])], [([-1, -1], [-1, 0]), ([1, -1], [1, -2]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([-1, 0, 0, -1], [-1, 1, -1, 0]), ([-1, 0, 0, 0], [-1, 1, -1, 1]), ([-1, 0, 0, 1], [-1, 1, -1, 2]), ([-1, 0, 1, -1], [-1, 1, 0, -3])], [([-1, 0], [-1, 1]), ([-1, -1, -1], [-1, 0, 0]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([0, -1, -1, 1], [0, -1, 1, 1]), ([0, -1, 0, -1], [0, -1, 2, -4]), ([0, -1, 0, 0], [0, -1, 2, -3]), ([0, -1, 0, 1], [0, -1, 2, -2])]]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("explicit oracle %d" % i, solve(args), expected)
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 |
|---|---|---|---|
| explicit oracle 0 | [] | [-1] | Failed |
| explicit oracle 1 | [1, 0, 0, 0] | [1, 0, 0, 0, 0] | Failed |
| explicit oracle 2 | [] | [0] | Failed |
| explicit oracle 3 | [] | [1] | Failed |
| explicit oracle 4 | [-1] | [-1, 0] | Failed |
| explicit oracle 5 | [-1] | [-1, 1] | Failed |
| explicit oracle 6 | [-1] | [-1, 2] | Failed |
| explicit oracle 7 | [0] | [0, -1] | Failed |
SHA-256 / 4d623494b2a469f9eb7c420c5393e69c9be7ef2e39b4d9166d3abdc3b31e4f7a
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
import itertools
from fractions import Fraction
N = 1
observations = []
def solve(x):
row=x[:];out=[]
for _ in range(1,len(x)):
if not row:break
out.append(row[0])
row=[row[i+1]-row[i] for i in range(len(row)-1)]
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([0], [0]), ([1], [1]), ([-1, -1], [-1, 0]), ([-1, 0], [-1, 1]), ([-1, 1], [-1, 2]), ([0, -1], [0, -1])], [([0], [0]), ([-1, -1], [-1, 0]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([-1, 0, 1], [-1, 1, 0]), ([-1, 1, -1], [-1, 2, -4]), ([-1, 1, 0], [-1, 2, -3]), ([-1, 1, 1], [-1, 2, -2])], [([1], [1]), ([0, -1], [0, -1]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([1, 0, 0], [1, -1, 1]), ([1, 0, 1], [1, -1, 2]), ([1, 1, -1], [1, 0, -2]), ([1, 1, 0], [1, 0, -1])], [([-1, -1], [-1, 0]), ([1, -1], [1, -2]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([-1, 0, 0, -1], [-1, 1, -1, 0]), ([-1, 0, 0, 0], [-1, 1, -1, 1]), ([-1, 0, 0, 1], [-1, 1, -1, 2]), ([-1, 0, 1, -1], [-1, 1, 0, -3])], [([-1, 0], [-1, 1]), ([-1, -1, -1], [-1, 0, 0]), ([-1], [-1]), ([1, 1, 1, 1, 1], [1, 0, 0, 0, 0]), ([0, -1, -1, 1], [0, -1, 1, 1]), ([0, -1, 0, -1], [0, -1, 2, -4]), ([0, -1, 0, 0], [0, -1, 2, -3]), ([0, -1, 0, 1], [0, -1, 2, -2])]]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("explicit oracle %d" % i, solve(args), expected)
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 |
|---|---|---|---|
| explicit oracle 0 | [] | [-1] | Failed |
| explicit oracle 1 | [1, 0, 0, 0] | [1, 0, 0, 0, 0] | Failed |
| explicit oracle 2 | [] | [0] | Failed |
| explicit oracle 3 | [] | [1] | Failed |
| explicit oracle 4 | [-1] | [-1, 0] | Failed |
| explicit oracle 5 | [-1] | [-1, 1] | Failed |
| explicit oracle 6 | [-1] | [-1, 2] | Failed |
| explicit oracle 7 | [0] | [0, -1] | Failed |
SHA-256 / 2b98036fc9138eaf8e6ee216802687baf4bc5fade321af9bf3eac76cd9b58c39
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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Sign in to the archive ↗Verification & scope
A deterministic bounded teaching model. Inputs are restricted to the explicit contract; this is not a production algebra library. 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 2026-09-29T14:39:19.737260+00:00.
Case digest / 8580f0f8ecfcfdf0032954247cae3684008355e3e29d02ff0e7e029f3a848feb