FA-66971 / Railway interlocking logic / Open access

Axle counter section supervision: sweep completion · case 01

The preparatory state ends before the sweep train has left the section.

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

ROOT CAUSE

Preparation is ended as soon as the sweep train counts in, not when it has counted out.

THE FAILURE

Preparation is ended as soon as the sweep train counts in, not when it has counted out.

Unsuccessful approach: Ending while one axle is still inside the section declares the section clear too early.

Case contract

An axle-counter section counts axles in and out. Counting out below zero latches disturbed (count forced to 0). A reset is accepted only when the section is disturbed or the count is non-zero; it zeroes the count and enters preparatory state, which ends only when a sweep train has counted in and the count returns to zero on an out-count. query reports disturbed, prep, occupied (count>0) or clear, in that precedence.

Why this case matters

Interlocking logic decides whether trains may be given authority; a wrong decision at this point either grants unsafe movements or strands traffic.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(x):
    count = 0
    disturbed = False
    prep = False
    swept = False
    out = []
    for ev in x['events']:
        if ev == 'in':
            count += 1
            if prep:
                prep = False
        elif ev == 'out':
            count -= 1
            if count < 0:
                disturbed = True
                count = 0
            if prep and swept and count == 0:
                prep = False
        elif ev == 'reset':
            if disturbed or count != 0:
                count = 0
                disturbed = False
                prep = True
                swept = False
        elif ev == 'query':
            if disturbed:
                out.append('disturbed')
            elif prep:
                out.append('prep')
            elif count > 0:
                out.append('occupied')
            else:
                out.append('clear')
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 9', {'events': ['in', 'query', 'query', 'reset', 'in', 'in', 'in', 'in', 'query', 'reset', 'in', 'query']}, ['occupied', 'occupied', 'prep', 'prep']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: under-count latches disturbance', {'events': ['out', 'query', 'in', 'query']}, ['disturbed', 'disturbed']), ('control 1', {'events': ['out', 'in', 'out', 'query', 'out', 'query', 'in', 'out', 'in', 'out', 'query', 'query', 'in', 'query', 'query']}, ['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']), ('control 4', {'events': ['in', 'out', 'query', 'query', 'query']}, ['clear', 'clear', 'clear']), ('control 7', {'events': ['query', 'out', 'in', 'query', 'out', 'query', 'reset', 'reset', 'in', 'reset', 'query', 'reset', 'query']}, ['clear', 'disturbed', 'disturbed', 'prep', 'prep'])], [('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 45', {'events': ['out', 'query', 'out', 'in', 'query', 'in', 'in', 'in', 'reset', 'in', 'query']}, ['disturbed', 'disturbed', 'prep']), ('boundary: reset of a disturbed section', {'events': ['out', 'reset', 'query', 'in', 'out', 'query']}, ['prep', 'clear']), ('boundary: reset refused on a clear section', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('boundary: under-count during preparation', {'events': ['in', 'reset', 'out', 'query']}, ['disturbed']), ('control 12', {'events': ['query', 'out', 'reset', 'out', 'query']}, ['clear', 'disturbed']), ('control 15', {'events': ['out', 'out', 'in', 'reset', 'query', 'query', 'query']}, ['prep', 'prep', 'prep']), ('sampled regression 18', {'events': ['out', 'query', 'query', 'reset', 'in', 'query', 'query']}, ['disturbed', 'disturbed', 'prep', 'prep'])], [('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 2', {'events': ['in', 'in', 'reset', 'reset', 'query', 'in', 'query']}, ['prep', 'prep']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: under-count during preparation', {'events': ['in', 'reset', 'out', 'query']}, ['disturbed']), ('control 23', {'events': ['query', 'out', 'query', 'out', 'in', 'in', 'in', 'query', 'out', 'in', 'in', 'query']}, ['clear', 'disturbed', 'disturbed', 'disturbed']), ('control 26', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('sampled regression 29', {'events': ['out', 'in', 'in', 'out', 'out', 'in', 'reset', 'out', 'reset', 'in', 'query', 'in', 'query']}, ['prep', 'prep'])], [('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: normal passage', {'events': ['in', 'in', 'query', 'out', 'out', 'query']}, ['occupied', 'clear']), ('boundary: under-count latches disturbance', {'events': ['out', 'query', 'in', 'query']}, ['disturbed', 'disturbed']), ('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('control 34', {'events': ['in', 'out', 'in', 'out', 'in', 'in', 'query']}, ['occupied']), ('control 37', {'events': ['reset', 'query', 'out', 'query', 'query', 'out', 'in', 'out', 'in', 'out', 'in', 'query']}, ['clear', 'disturbed', 'disturbed', 'disturbed']), ('control 40', {'events': ['in', 'in', 'query', 'out', 'query']}, ['occupied', 'occupied'])], [('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: reset of a disturbed section', {'events': ['out', 'reset', 'query', 'in', 'out', 'query']}, ['prep', 'clear']), ('boundary: reset refused on a clear section', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('sampled regression 45', {'events': ['out', 'query', 'out', 'in', 'query', 'in', 'in', 'in', 'reset', 'in', 'query']}, ['disturbed', 'disturbed', 'prep']), ('sampled regression 48', {'events': ['out', 'query', 'in', 'out', 'reset', 'in', 'query', 'query', 'query', 'query']}, ['disturbed', 'prep', 'prep', 'prep', 'prep']), ('control 51', {'events': ['reset', 'query', 'in', 'out', 'query', 'in', 'in', 'query', 'query', 'query', 'query']}, ['clear', 'clear', 'occupied', 'occupied', 'occupied', 'occupied'])]]
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: reset of a miscounted section	`['prep', 'occupied', 'clear']`	`['prep', 'prep', 'clear']`	Failed
regression: sweep train partly through	`['occupied', 'clear']`	`['prep', 'clear']`	Failed
sampled regression 9	`['occupied', 'occupied', 'occupied', 'occupied']`	`['occupied', 'occupied', 'prep', 'prep']`	Failed
sampled regression 39	`['clear', 'clear', 'clear', 'clear', 'clear', 'occupied']`	`['clear', 'clear', 'clear', 'clear', 'clear', 'prep']`	Failed
boundary: under-count latches disturbance	`['disturbed', 'disturbed']`	`['disturbed', 'disturbed']`	Passed
control 1	`['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']`	`['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']`	Passed
control 4	`['clear', 'clear', 'clear']`	`['clear', 'clear', 'clear']`	Passed
control 7	`['clear', 'disturbed', 'disturbed', 'prep', 'prep']`	`['clear', 'disturbed', 'disturbed', 'prep', 'prep']`	Passed

SHA-256 / 0bc26fe3444ba1e6c2f1ee17df020f5a18740b39aa29ba23e2768908ba340b16

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(x):
    count = 0
    disturbed = False
    prep = False
    swept = False
    out = []
    for ev in x['events']:
        if ev == 'in':
            count += 1
            if prep:
                swept = True
        elif ev == 'out':
            count -= 1
            if count < 0:
                disturbed = True
                count = 0
            if prep and swept and count <= 1:
                prep = False
        elif ev == 'reset':
            if disturbed or count != 0:
                count = 0
                disturbed = False
                prep = True
                swept = False
        elif ev == 'query':
            if disturbed:
                out.append('disturbed')
            elif prep:
                out.append('prep')
            elif count > 0:
                out.append('occupied')
            else:
                out.append('clear')
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 9', {'events': ['in', 'query', 'query', 'reset', 'in', 'in', 'in', 'in', 'query', 'reset', 'in', 'query']}, ['occupied', 'occupied', 'prep', 'prep']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: under-count latches disturbance', {'events': ['out', 'query', 'in', 'query']}, ['disturbed', 'disturbed']), ('control 1', {'events': ['out', 'in', 'out', 'query', 'out', 'query', 'in', 'out', 'in', 'out', 'query', 'query', 'in', 'query', 'query']}, ['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']), ('control 4', {'events': ['in', 'out', 'query', 'query', 'query']}, ['clear', 'clear', 'clear']), ('control 7', {'events': ['query', 'out', 'in', 'query', 'out', 'query', 'reset', 'reset', 'in', 'reset', 'query', 'reset', 'query']}, ['clear', 'disturbed', 'disturbed', 'prep', 'prep'])], [('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 45', {'events': ['out', 'query', 'out', 'in', 'query', 'in', 'in', 'in', 'reset', 'in', 'query']}, ['disturbed', 'disturbed', 'prep']), ('boundary: reset of a disturbed section', {'events': ['out', 'reset', 'query', 'in', 'out', 'query']}, ['prep', 'clear']), ('boundary: reset refused on a clear section', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('boundary: under-count during preparation', {'events': ['in', 'reset', 'out', 'query']}, ['disturbed']), ('control 12', {'events': ['query', 'out', 'reset', 'out', 'query']}, ['clear', 'disturbed']), ('control 15', {'events': ['out', 'out', 'in', 'reset', 'query', 'query', 'query']}, ['prep', 'prep', 'prep']), ('sampled regression 18', {'events': ['out', 'query', 'query', 'reset', 'in', 'query', 'query']}, ['disturbed', 'disturbed', 'prep', 'prep'])], [('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 2', {'events': ['in', 'in', 'reset', 'reset', 'query', 'in', 'query']}, ['prep', 'prep']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: under-count during preparation', {'events': ['in', 'reset', 'out', 'query']}, ['disturbed']), ('control 23', {'events': ['query', 'out', 'query', 'out', 'in', 'in', 'in', 'query', 'out', 'in', 'in', 'query']}, ['clear', 'disturbed', 'disturbed', 'disturbed']), ('control 26', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('sampled regression 29', {'events': ['out', 'in', 'in', 'out', 'out', 'in', 'reset', 'out', 'reset', 'in', 'query', 'in', 'query']}, ['prep', 'prep'])], [('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: normal passage', {'events': ['in', 'in', 'query', 'out', 'out', 'query']}, ['occupied', 'clear']), ('boundary: under-count latches disturbance', {'events': ['out', 'query', 'in', 'query']}, ['disturbed', 'disturbed']), ('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('control 34', {'events': ['in', 'out', 'in', 'out', 'in', 'in', 'query']}, ['occupied']), ('control 37', {'events': ['reset', 'query', 'out', 'query', 'query', 'out', 'in', 'out', 'in', 'out', 'in', 'query']}, ['clear', 'disturbed', 'disturbed', 'disturbed']), ('control 40', {'events': ['in', 'in', 'query', 'out', 'query']}, ['occupied', 'occupied'])], [('regression: reset of a miscounted section', {'events': ['in', 'in', 'out', 'reset', 'query', 'in', 'in', 'query', 'out', 'out', 'query']}, ['prep', 'prep', 'clear']), ('regression: sweep train partly through', {'events': ['out', 'reset', 'in', 'in', 'out', 'query', 'out', 'query']}, ['prep', 'clear']), ('sampled regression 39', {'events': ['query', 'query', 'query', 'query', 'query', 'reset', 'out', 'out', 'out', 'reset', 'in', 'in', 'out', 'query']}, ['clear', 'clear', 'clear', 'clear', 'clear', 'prep']), ('boundary: reset of a disturbed section', {'events': ['out', 'reset', 'query', 'in', 'out', 'query']}, ['prep', 'clear']), ('boundary: reset refused on a clear section', {'events': ['reset', 'query', 'in', 'query']}, ['clear', 'occupied']), ('sampled regression 45', {'events': ['out', 'query', 'out', 'in', 'query', 'in', 'in', 'in', 'reset', 'in', 'query']}, ['disturbed', 'disturbed', 'prep']), ('sampled regression 48', {'events': ['out', 'query', 'in', 'out', 'reset', 'in', 'query', 'query', 'query', 'query']}, ['disturbed', 'prep', 'prep', 'prep', 'prep']), ('control 51', {'events': ['reset', 'query', 'in', 'out', 'query', 'in', 'in', 'query', 'query', 'query', 'query']}, ['clear', 'clear', 'occupied', 'occupied', 'occupied', 'occupied'])]]
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: reset of a miscounted section	`['prep', 'prep', 'clear']`	`['prep', 'prep', 'clear']`	Passed
regression: sweep train partly through	`['occupied', 'clear']`	`['prep', 'clear']`	Failed
sampled regression 9	`['occupied', 'occupied', 'prep', 'prep']`	`['occupied', 'occupied', 'prep', 'prep']`	Passed
sampled regression 39	`['clear', 'clear', 'clear', 'clear', 'clear', 'occupied']`	`['clear', 'clear', 'clear', 'clear', 'clear', 'prep']`	Failed
boundary: under-count latches disturbance	`['disturbed', 'disturbed']`	`['disturbed', 'disturbed']`	Passed
control 1	`['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']`	`['disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed', 'disturbed']`	Passed
control 4	`['clear', 'clear', 'clear']`	`['clear', 'clear', 'clear']`	Passed
control 7	`['clear', 'disturbed', 'disturbed', 'prep', 'prep']`	`['clear', 'disturbed', 'disturbed', 'prep', 'prep']`	Passed

SHA-256 / f9b4091868d41c820031e97e0a95345a0eacc53b972f00ba0ac7c3a6fbe44fa1

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.

Member access is invitation-based. Sign in with your invited account to inspect the repair.

Verification & scope

Stipulated toy interlocking contract for a bounded teaching model; it makes no claim of conformance to any railway signalling standard and omits real safety cases. 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 2026-09-29T14:47:48.644520+00:00.

Case digest / 8a9026f43cf797671e0f8f854db1545bf04c118bfa037422cd17852099430b5c