FA-92071 / PLC ladder logic scan cycles / Open access

Watchdog fault time is reported at the end of the overrunning execution · case 01

The major fault is logged later than it occurred, after the watchdog should already have stopped the task.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The fault time adds the full execution time rather than the watchdog limit to the start time.

VERIFIED REPAIR

The fault occurs at start time + watchdog.

Unsuccessful approach: Reporting the watchdog limit alone drops the task start time.

Case contract

Periodic task triggered every period ms from t=0; exec_times[k] is how long the k-th triggered execution would take. A trigger arriving while the previous execution is still running (trigger time < completion time) is an overlap: it is counted and skipped, not queued; a trigger exactly at completion starts normally. An execution longer than watchdog raises a major fault at start + watchdog and scheduling stops. Return [start_times, overlap_count, fault_time or None].

Why this case matters

Ladder programs are executed as repeated scans; each defect here changes what a rung, timer, counter or data-table instruction reports on a particular scan, which is how commissioning and field faults are actually observed.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(period, watchdog, exec_times):
    t_free = 0
    starts = []
    overlaps = 0
    fault = None
    for k, ex in enumerate(exec_times):
        trig = k * period
        if trig < t_free:
            overlaps += 1
            continue
        starts.append(trig)
        if ex > watchdog:
            fault = trig + ex
            break
        t_free = trig + ex
    return [starts, overlaps, fault]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['regression: scenario 4',
   [50, 60, [21, 100, 100, 60, 100, 100, 60, 60, 45, 50, 100, 100]],
   [[0, 50], 0, 110]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [50, 100, [100, 100, 100, 100, 50, 25]], [[0, 100, 200, 250], 2, None]],
  ['control: scenario 2', [20, 100, [100, 100, 60, 39, 20, 40, 54, 40]], [[0, 100, 140], 5, None]]],
 [['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['regression: scenario 4', [10, 30, [20, 20, 51, 30, 26, 20, 54, 2]], [[0, 20], 1, 50]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 60, [60, 20, 36, 40, 20]], [[0, 60], 3, None]],
  ['control: scenario 2',
   [10, 100, [10, 10, 10, 10, 10, 20, 100, 3, 20, 10, 100]],
   [[0, 10, 20, 30, 40, 50, 70, 80, 100], 2, None]]],
 [['regression: scenario 2', [10, 40, [50, 40, 10, 40, 10, 61, 60, 40, 20, 20, 10, 10]], [[0], 0, 40]],
  ['regression: scenario 4', [25, 30, [30, 30, 6, 16, 50, 30]], [[0, 50, 75, 100], 1, 130]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 100, [100, 20, 60, 100, 40, 20, 30, 12]], [[0, 100, 120], 5, None]]],
 [['regression: scenario 3',
   [10, 40, [20, 20, 20, 20, 10, 61, 55, 66, 20, 37, 40, 40]],
   [[0, 20, 40, 50], 2, 90]],
  ['regression: scenario 22', [25, 40, [25, 64, 50, 50, 40, 67, 25]], [[0, 25], 0, 65]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1',
   [20, 30, [21, 20, 20, 20, 40, 30, 20, 30, 40, 30, 40]],
   [[0, 40, 60, 80], 1, 110]]],
 [['regression: scenario 3', [50, 30, [50, 50, 100, 30, 25, 30, 50, 100]], [[0], 0, 30]],
  ['regression: scenario 13', [50, 40, [40, 50, 50, 10, 50, 100, 40, 20, 37, 41]], [[0, 50], 0, 90]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1', [25, 60, [70, 25, 60, 35, 25, 15, 60, 60, 25, 50, 25, 4]], [[0], 0, 60]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
regression: watchdog exceeded	`[[0, 10], 0, 23]`	`[[0, 10], 0, 22]`	Failed
regression: scenario 4	`[[0, 50], 0, 150]`	`[[0, 50], 0, 110]`	Failed
control: mixed overlaps	`[[0, 10, 30, 40], 2, None]`	`[[0, 10, 30, 40], 2, None]`	Passed
control: exact watchdog	`[[0, 40, 60], 1, None]`	`[[0, 40, 60], 1, None]`	Passed
regression: first execution overruns	`[[0], 0, 30]`	`[[0], 0, 25]`	Failed
control: skip then drift	`[[0, 30, 40, 50], 2, None]`	`[[0, 30, 40, 50], 2, None]`	Passed
control: scenario 1	`[[0, 100, 200, 250], 2, None]`	`[[0, 100, 200, 250], 2, None]`	Passed
control: scenario 2	`[[0, 100, 140], 5, None]`	`[[0, 100, 140], 5, None]`	Passed

SHA-256 / c55ff300918faa46dabab84623434f042c565c9afefe4f421edf1ea0a42a8848

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(period, watchdog, exec_times):
    t_free = 0
    starts = []
    overlaps = 0
    fault = None
    for k, ex in enumerate(exec_times):
        trig = k * period
        if trig < t_free:
            overlaps += 1
            continue
        starts.append(trig)
        if ex > watchdog:
            fault = watchdog
            break
        t_free = trig + ex
    return [starts, overlaps, fault]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['regression: scenario 4',
   [50, 60, [21, 100, 100, 60, 100, 100, 60, 60, 45, 50, 100, 100]],
   [[0, 50], 0, 110]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [50, 100, [100, 100, 100, 100, 50, 25]], [[0, 100, 200, 250], 2, None]],
  ['control: scenario 2', [20, 100, [100, 100, 60, 39, 20, 40, 54, 40]], [[0, 100, 140], 5, None]]],
 [['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['regression: scenario 4', [10, 30, [20, 20, 51, 30, 26, 20, 54, 2]], [[0, 20], 1, 50]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 60, [60, 20, 36, 40, 20]], [[0, 60], 3, None]],
  ['control: scenario 2',
   [10, 100, [10, 10, 10, 10, 10, 20, 100, 3, 20, 10, 100]],
   [[0, 10, 20, 30, 40, 50, 70, 80, 100], 2, None]]],
 [['regression: scenario 2', [10, 40, [50, 40, 10, 40, 10, 61, 60, 40, 20, 20, 10, 10]], [[0], 0, 40]],
  ['regression: scenario 4', [25, 30, [30, 30, 6, 16, 50, 30]], [[0, 50, 75, 100], 1, 130]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 100, [100, 20, 60, 100, 40, 20, 30, 12]], [[0, 100, 120], 5, None]]],
 [['regression: scenario 3',
   [10, 40, [20, 20, 20, 20, 10, 61, 55, 66, 20, 37, 40, 40]],
   [[0, 20, 40, 50], 2, 90]],
  ['regression: scenario 22', [25, 40, [25, 64, 50, 50, 40, 67, 25]], [[0, 25], 0, 65]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1',
   [20, 30, [21, 20, 20, 20, 40, 30, 20, 30, 40, 30, 40]],
   [[0, 40, 60, 80], 1, 110]]],
 [['regression: scenario 3', [50, 30, [50, 50, 100, 30, 25, 30, 50, 100]], [[0], 0, 30]],
  ['regression: scenario 13', [50, 40, [40, 50, 50, 10, 50, 100, 40, 20, 37, 41]], [[0, 50], 0, 90]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1', [25, 60, [70, 25, 60, 35, 25, 15, 60, 60, 25, 50, 25, 4]], [[0], 0, 60]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
regression: watchdog exceeded	`[[0, 10], 0, 12]`	`[[0, 10], 0, 22]`	Failed
regression: scenario 4	`[[0, 50], 0, 60]`	`[[0, 50], 0, 110]`	Failed
control: mixed overlaps	`[[0, 10, 30, 40], 2, None]`	`[[0, 10, 30, 40], 2, None]`	Passed
control: exact watchdog	`[[0, 40, 60], 1, None]`	`[[0, 40, 60], 1, None]`	Passed
regression: first execution overruns	`[[0], 0, 25]`	`[[0], 0, 25]`	Passed
control: skip then drift	`[[0, 30, 40, 50], 2, None]`	`[[0, 30, 40, 50], 2, None]`	Passed
control: scenario 1	`[[0, 100, 200, 250], 2, None]`	`[[0, 100, 200, 250], 2, None]`	Passed
control: scenario 2	`[[0, 100, 140], 5, None]`	`[[0, 100, 140], 5, None]`	Passed

SHA-256 / 5d2b49ffb2ed235e03f16c3ffe0585e162e09ceb017b40f2b4c24913310b0f03

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(period, watchdog, exec_times):
    t_free = 0
    starts = []
    overlaps = 0
    fault = None
    for k, ex in enumerate(exec_times):
        trig = k * period
        if trig < t_free:
            overlaps += 1
            continue
        starts.append(trig)
        if ex > watchdog:
            fault = trig + watchdog
            break
        t_free = trig + ex
    return [starts, overlaps, fault]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['regression: scenario 4',
   [50, 60, [21, 100, 100, 60, 100, 100, 60, 60, 45, 50, 100, 100]],
   [[0, 50], 0, 110]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [50, 100, [100, 100, 100, 100, 50, 25]], [[0, 100, 200, 250], 2, None]],
  ['control: scenario 2', [20, 100, [100, 100, 60, 39, 20, 40, 54, 40]], [[0, 100, 140], 5, None]]],
 [['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['regression: scenario 4', [10, 30, [20, 20, 51, 30, 26, 20, 54, 2]], [[0, 20], 1, 50]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 60, [60, 20, 36, 40, 20]], [[0, 60], 3, None]],
  ['control: scenario 2',
   [10, 100, [10, 10, 10, 10, 10, 20, 100, 3, 20, 10, 100]],
   [[0, 10, 20, 30, 40, 50, 70, 80, 100], 2, None]]],
 [['regression: scenario 2', [10, 40, [50, 40, 10, 40, 10, 61, 60, 40, 20, 20, 10, 10]], [[0], 0, 40]],
  ['regression: scenario 4', [25, 30, [30, 30, 6, 16, 50, 30]], [[0, 50, 75, 100], 1, 130]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['control: scenario 1', [20, 100, [100, 20, 60, 100, 40, 20, 30, 12]], [[0, 100, 120], 5, None]]],
 [['regression: scenario 3',
   [10, 40, [20, 20, 20, 20, 10, 61, 55, 66, 20, 37, 40, 40]],
   [[0, 20, 40, 50], 2, 90]],
  ['regression: scenario 22', [25, 40, [25, 64, 50, 50, 40, 67, 25]], [[0, 25], 0, 65]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1',
   [20, 30, [21, 20, 20, 20, 40, 30, 20, 30, 40, 30, 40]],
   [[0, 40, 60, 80], 1, 110]]],
 [['regression: scenario 3', [50, 30, [50, 50, 100, 30, 25, 30, 50, 100]], [[0], 0, 30]],
  ['regression: scenario 13', [50, 40, [40, 50, 50, 10, 50, 100, 40, 20, 37, 41]], [[0, 50], 0, 90]],
  ['control: mixed overlaps', [10, 50, [5, 15, 3, 10, 12, 4]], [[0, 10, 30, 40], 2, None]],
  ['regression: watchdog exceeded', [10, 12, [5, 13, 4]], [[0, 10], 0, 22]],
  ['control: exact watchdog', [20, 30, [30, 5, 5, 5]], [[0, 40, 60], 1, None]],
  ['regression: first execution overruns', [10, 25, [30, 5]], [[0], 0, 25]],
  ['control: skip then drift', [10, 100, [25, 1, 1, 1, 1, 1]], [[0, 30, 40, 50], 2, None]],
  ['regression: scenario 1', [25, 60, [70, 25, 60, 35, 25, 15, 60, 60, 25, 50, 25, 4]], [[0], 0, 60]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
regression: watchdog exceeded	`[[0, 10], 0, 22]`	`[[0, 10], 0, 22]`	Passed
regression: scenario 4	`[[0, 50], 0, 110]`	`[[0, 50], 0, 110]`	Passed
control: mixed overlaps	`[[0, 10, 30, 40], 2, None]`	`[[0, 10, 30, 40], 2, None]`	Passed
control: exact watchdog	`[[0, 40, 60], 1, None]`	`[[0, 40, 60], 1, None]`	Passed
regression: first execution overruns	`[[0], 0, 25]`	`[[0], 0, 25]`	Passed
control: skip then drift	`[[0, 30, 40, 50], 2, None]`	`[[0, 30, 40, 50], 2, None]`	Passed
control: scenario 1	`[[0, 100, 200, 250], 2, None]`	`[[0, 100, 200, 250], 2, None]`	Passed
control: scenario 2	`[[0, 100, 140], 5, None]`	`[[0, 100, 140], 5, None]`	Passed

SHA-256 / 7619cf21a96a905c75a198f108394518ac67a9d6261372371c09f555ab183710

Verification & scope

A deterministic bounded teaching model of one PLC instruction or rung pattern evaluated scan by scan. The stated contract is a stipulated toy convention, not a claim of conformance to any vendor controller or IEC 61131-3 runtime. 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 2026-09-29T14:51:42.328781+00:00.

Case digest / f3d5a8c46e97df068f92f588cd7caf29bb38b475c5adad34ce4be2820bef6752