FA-17591 / Time representation / Open access
Negative phase debt contributes a negative correction magnitude · case 01
The decoded time state disagrees with the explicit regression oracle for magnitude.
ROOT CAUSE
Negative phase debt contributes a negative correction magnitude.
VERIFIED REPAIR
Preserve the declared coordinate and state contract at magnitude: magnitude = abs(r['debt']).
Unsuccessful approach: The partial correction still substitutes max(0,r['debt']) 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 = 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 | [-20, 113, False, -4, 6] | [-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 / 80361cbd448d8ecfdeaa4d956eafab9846999c126c60f53b7de7c52f4f153799
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 = max(0,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 | [-10, 103, False, 6, -4] | [-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 | [-2, -5, False, 5, 7] | [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 | [-3, 6, False, 4, -1] | [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 / ecd3fef82a588f23893ea8de22408abdffc5c96563ddce1a3b9477846ffe4551
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 2026-09-29T14:39:48.361909+00:00.
Case digest / 1ab0032063ad8702fc4dbf25bb18c280dbaacee339f97272e6953899079f4e24