FA-17606 / Time representation / Open access
Slew step exceeds correction cap or loses debt direction · case 01
The decoded time state disagrees with the explicit regression oracle for applied.
ROOT CAUSE
Slew step exceeds correction cap or loses debt direction.
VERIFIED REPAIR
Preserve the declared coordinate and state contract at applied: applied = direction * min(magnitude,capacity).
Unsuccessful approach: The partial correction still substitutes min(magnitude,capacity) at the same fault site.
Case contract
Slew signed phase debt at capacity elapsed*rate without changing ordinary elapsed advancement. Return signed remaining debt, new wall coordinate, completion flag, unused correction capacity and signed cumulative correction. Elapsed and rate are nonnegative integers; wall and debt may be signed.
Why this case matters
Clock transfer and timestamp consumers require preserved coordinate, phase, validity and elapsed-time semantics.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(r):
magnitude = abs(r['debt'])
capacity = r['elapsed'] * r['rate']
direction = (r['debt'] > 0) - (r['debt'] < 0)
applied = direction * max(magnitude,capacity)
remaining = r['debt'] - applied
advance = r['elapsed'] + applied
wall = r['wall'] + advance
complete = remaining == 0
unused = capacity - abs(applied)
cumulative = r['prior_correction'] + applied
return [remaining,wall,complete,unused,cumulative]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 4}), [4, 109, False, 0, 10])
check('fixture 2', solve({'debt': -10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': -4}), [-4, 97, False, 0, -10])
check('fixture 3', solve({'debt': 4, 'elapsed': 2, 'rate': 2, 'wall': 20, 'prior_correction': 0}), [0, 26, True, 0, 4])
check('fixture 4', solve({'debt': 0, 'elapsed': 3, 'rate': 1, 'wall': 10, 'prior_correction': 8}), [0, 13, True, 3, 8])
check('fixture 5', solve({'debt': 3, 'elapsed': 0, 'rate': 2, 'wall': 50, 'prior_correction': 2}), [3, 50, False, 0, 2])
check('fixture 6', solve({'debt': -2, 'elapsed': 5, 'rate': 1, 'wall': -10, 'prior_correction': 7}), [0, -7, True, 3, 5])
check('fixture 7', solve({'debt': 20, 'elapsed': 4, 'rate': 0, 'wall': 100, 'prior_correction': 3}), [20, 104, False, 0, 3])
check('fixture 8', solve({'debt': 1, 'elapsed': 3, 'rate': 2, 'wall': 0, 'prior_correction': -1}), [0, 4, True, 5, 0])
check('fixture 9', solve({'debt': -3, 'elapsed': 2, 'rate': 2, 'wall': 4, 'prior_correction': -1}), [0, 3, True, 1, -4])
check('fixture 10', solve({'debt': 0, 'elapsed': 0, 'rate': 0, 'wall': 0, 'prior_correction': 0}), [0, 0, True, 0, 0])
variant = [({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 5}, [4, 109, False, 0, 11]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 6}, [4, 109, False, 0, 12]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 7}, [4, 109, False, 0, 13]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 8}, [4, 109, False, 0, 14]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 9}, [4, 109, False, 0, 15])]
check("variant capture", solve(variant[N-1][0]), variant[N-1][1])
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 |
|---|---|---|---|
| fixture 1 | [0, 113, True, -4, 14] | [4, 109, False, 0, 10] | Failed |
| fixture 2 | [0, 93, True, -4, -14] | [-4, 97, False, 0, -10] | Failed |
| fixture 3 | [0, 26, True, 0, 4] | [0, 26, True, 0, 4] | Passed |
| fixture 4 | [0, 13, True, 3, 8] | [0, 13, True, 3, 8] | Passed |
| fixture 5 | [0, 53, True, -3, 5] | [3, 50, False, 0, 2] | Failed |
| fixture 6 | [3, -10, False, 0, 2] | [0, -7, True, 3, 5] | Failed |
| fixture 7 | [0, 124, True, -20, 23] | [20, 104, False, 0, 3] | Failed |
| fixture 8 | [-5, 9, False, 0, 5] | [0, 4, True, 5, 0] | Failed |
| fixture 9 | [1, 2, False, 0, -5] | [0, 3, True, 1, -4] | Failed |
| fixture 10 | [0, 0, True, 0, 0] | [0, 0, True, 0, 0] | Passed |
| variant capture | [0, 113, True, -4, 15] | [4, 109, False, 0, 11] | Failed |
SHA-256 / 1b67be1d3a55fd9d980f2ae7a3406d03a86f333a49f9569edf98a1decdf2874b
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(r):
magnitude = abs(r['debt'])
capacity = r['elapsed'] * r['rate']
direction = (r['debt'] > 0) - (r['debt'] < 0)
applied = min(magnitude,capacity)
remaining = r['debt'] - applied
advance = r['elapsed'] + applied
wall = r['wall'] + advance
complete = remaining == 0
unused = capacity - abs(applied)
cumulative = r['prior_correction'] + applied
return [remaining,wall,complete,unused,cumulative]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 4}), [4, 109, False, 0, 10])
check('fixture 2', solve({'debt': -10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': -4}), [-4, 97, False, 0, -10])
check('fixture 3', solve({'debt': 4, 'elapsed': 2, 'rate': 2, 'wall': 20, 'prior_correction': 0}), [0, 26, True, 0, 4])
check('fixture 4', solve({'debt': 0, 'elapsed': 3, 'rate': 1, 'wall': 10, 'prior_correction': 8}), [0, 13, True, 3, 8])
check('fixture 5', solve({'debt': 3, 'elapsed': 0, 'rate': 2, 'wall': 50, 'prior_correction': 2}), [3, 50, False, 0, 2])
check('fixture 6', solve({'debt': -2, 'elapsed': 5, 'rate': 1, 'wall': -10, 'prior_correction': 7}), [0, -7, True, 3, 5])
check('fixture 7', solve({'debt': 20, 'elapsed': 4, 'rate': 0, 'wall': 100, 'prior_correction': 3}), [20, 104, False, 0, 3])
check('fixture 8', solve({'debt': 1, 'elapsed': 3, 'rate': 2, 'wall': 0, 'prior_correction': -1}), [0, 4, True, 5, 0])
check('fixture 9', solve({'debt': -3, 'elapsed': 2, 'rate': 2, 'wall': 4, 'prior_correction': -1}), [0, 3, True, 1, -4])
check('fixture 10', solve({'debt': 0, 'elapsed': 0, 'rate': 0, 'wall': 0, 'prior_correction': 0}), [0, 0, True, 0, 0])
variant = [({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 5}, [4, 109, False, 0, 11]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 6}, [4, 109, False, 0, 12]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 7}, [4, 109, False, 0, 13]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 8}, [4, 109, False, 0, 14]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 9}, [4, 109, False, 0, 15])]
check("variant capture", solve(variant[N-1][0]), variant[N-1][1])
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 |
|---|---|---|---|
| fixture 1 | [4, 109, False, 0, 10] | [4, 109, False, 0, 10] | Passed |
| fixture 2 | [-16, 109, False, 0, 2] | [-4, 97, False, 0, -10] | Failed |
| fixture 3 | [0, 26, True, 0, 4] | [0, 26, True, 0, 4] | Passed |
| fixture 4 | [0, 13, True, 3, 8] | [0, 13, True, 3, 8] | Passed |
| fixture 5 | [3, 50, False, 0, 2] | [3, 50, False, 0, 2] | Passed |
| fixture 6 | [-4, -3, False, 3, 9] | [0, -7, True, 3, 5] | Failed |
| fixture 7 | [20, 104, False, 0, 3] | [20, 104, False, 0, 3] | Passed |
| fixture 8 | [0, 4, True, 5, 0] | [0, 4, True, 5, 0] | Passed |
| fixture 9 | [-6, 9, False, 1, 2] | [0, 3, True, 1, -4] | Failed |
| fixture 10 | [0, 0, True, 0, 0] | [0, 0, True, 0, 0] | Passed |
| variant capture | [4, 109, False, 0, 11] | [4, 109, False, 0, 11] | Passed |
SHA-256 / 1e190b796dcb920f6980d92ef23d8b55e8087d556e543529605bdf5bf947fa35
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(r):
magnitude = abs(r['debt'])
capacity = r['elapsed'] * r['rate']
direction = (r['debt'] > 0) - (r['debt'] < 0)
applied = direction * min(magnitude,capacity)
remaining = r['debt'] - applied
advance = r['elapsed'] + applied
wall = r['wall'] + advance
complete = remaining == 0
unused = capacity - abs(applied)
cumulative = r['prior_correction'] + applied
return [remaining,wall,complete,unused,cumulative]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 4}), [4, 109, False, 0, 10])
check('fixture 2', solve({'debt': -10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': -4}), [-4, 97, False, 0, -10])
check('fixture 3', solve({'debt': 4, 'elapsed': 2, 'rate': 2, 'wall': 20, 'prior_correction': 0}), [0, 26, True, 0, 4])
check('fixture 4', solve({'debt': 0, 'elapsed': 3, 'rate': 1, 'wall': 10, 'prior_correction': 8}), [0, 13, True, 3, 8])
check('fixture 5', solve({'debt': 3, 'elapsed': 0, 'rate': 2, 'wall': 50, 'prior_correction': 2}), [3, 50, False, 0, 2])
check('fixture 6', solve({'debt': -2, 'elapsed': 5, 'rate': 1, 'wall': -10, 'prior_correction': 7}), [0, -7, True, 3, 5])
check('fixture 7', solve({'debt': 20, 'elapsed': 4, 'rate': 0, 'wall': 100, 'prior_correction': 3}), [20, 104, False, 0, 3])
check('fixture 8', solve({'debt': 1, 'elapsed': 3, 'rate': 2, 'wall': 0, 'prior_correction': -1}), [0, 4, True, 5, 0])
check('fixture 9', solve({'debt': -3, 'elapsed': 2, 'rate': 2, 'wall': 4, 'prior_correction': -1}), [0, 3, True, 1, -4])
check('fixture 10', solve({'debt': 0, 'elapsed': 0, 'rate': 0, 'wall': 0, 'prior_correction': 0}), [0, 0, True, 0, 0])
variant = [({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 5}, [4, 109, False, 0, 11]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 6}, [4, 109, False, 0, 12]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 7}, [4, 109, False, 0, 13]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 8}, [4, 109, False, 0, 14]), ({'debt': 10, 'elapsed': 3, 'rate': 2, 'wall': 100, 'prior_correction': 9}, [4, 109, False, 0, 15])]
check("variant capture", solve(variant[N-1][0]), variant[N-1][1])
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 |
|---|---|---|---|
| fixture 1 | [4, 109, False, 0, 10] | [4, 109, False, 0, 10] | Passed |
| fixture 2 | [-4, 97, False, 0, -10] | [-4, 97, False, 0, -10] | Passed |
| fixture 3 | [0, 26, True, 0, 4] | [0, 26, True, 0, 4] | Passed |
| fixture 4 | [0, 13, True, 3, 8] | [0, 13, True, 3, 8] | Passed |
| fixture 5 | [3, 50, False, 0, 2] | [3, 50, False, 0, 2] | Passed |
| fixture 6 | [0, -7, True, 3, 5] | [0, -7, True, 3, 5] | Passed |
| fixture 7 | [20, 104, False, 0, 3] | [20, 104, False, 0, 3] | Passed |
| fixture 8 | [0, 4, True, 5, 0] | [0, 4, True, 5, 0] | Passed |
| fixture 9 | [0, 3, True, 1, -4] | [0, 3, True, 1, -4] | Passed |
| fixture 10 | [0, 0, True, 0, 0] | [0, 0, True, 0, 0] | Passed |
| variant capture | [4, 109, False, 0, 11] | [4, 109, False, 0, 11] | Passed |
SHA-256 / 14d8e8fd4aa1019ef970fa4af98fbd91e780cb0805c133c11dc271a378f706e9
Verification & scope
Deterministic integer reference model with stipulated units and policies; not a complete clock, wire standard or platform implementation. 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 2026-09-29T14:39:48.393507+00:00.
Case digest / fa71ffcbc464bb3fa89016c3703eb99aa33701ae57ea163b432d93c019f813e6