FA-67096 / Railway interlocking logic / Open access

Movement authority end computation: length cap reference · case 01

The authority is cut short of max_ma_m ahead of the train.

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

ROOT CAUSE

The length cap is measured from the start of the train's section instead of from its front.

VERIFIED REPAIR

Measure the maximum length from the train front and cut only when it is exceeded.

Unsuccessful approach: An inclusive comparison labels an authority that exactly reaches the obstacle as a max-length cut and drops the margin.

Case contract

Sections have lengths and states locked, occupied or unlocked; the train front is offset_m into section train_sec (which it occupies itself). Scan the following sections; the end of authority is the start of the first section that is not locked (reason = its state) or the end of the last section (end-of-route). If that exceeds max_ma_m ahead of the train front, the authority is cut to front + max_ma_m (reason max-length). The margin is subtracted from the end except for a max-length cut.

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):
    secs = x['sections']
    bounds = []
    acc = 0
    for s in secs:
        bounds.append(acc)
        acc += s['len']
    k = x['train_sec']
    eoa = acc
    reason = 'end-of-route'
    for j in range(k + 1, len(secs)):
        if secs[j]['state'] != 'locked':
            eoa = bounds[j]
            reason = secs[j]['state']
            break
    front = bounds[k] + x['offset_m']
    if eoa - bounds[k] > x['max_ma_m']:
        eoa = bounds[k] + x['max_ma_m']
        reason = 'max-length'
    if reason != 'max-length':
        eoa -= x['margin_m']
    return {'eoa_m': eoa, 'reason': reason}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 1', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 69, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'unlocked'}), ('control 4', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 206, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 1325, 'reason': 'end-of-route'}), ('control 7', {'sections': [{'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 500, 'state': 'unlocked'}, {'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 108, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 550, 'reason': 'unlocked'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('control 15', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 4, 'offset_m': 137, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 2100, 'reason': 'end-of-route'}), ('control 18', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 3, 'offset_m': 181, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 1250, 'reason': 'occupied'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 70', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 212, 'max_ma_m': 300, 'margin_m': 0}, {'eoa_m': 512, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('control 23', {'sections': [{'len': 350, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 1100, 'reason': 'unlocked'}), ('sampled regression 26', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 9, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 409, 'reason': 'max-length'}), ('sampled regression 29', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 288, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 1000, 'reason': 'occupied'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 34', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 222, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 850, 'reason': 'unlocked'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('control 40', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 500, 'state': 'unlocked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 25, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 500, 'reason': 'unlocked'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('sampled regression 45', {'sections': [{'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 348, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 1198, 'reason': 'max-length'}), ('sampled regression 48', {'sections': [{'len': 500, 'state': 'unlocked'}, {'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 200, 'max_ma_m': 1000, 'margin_m': 25}, {'eoa_m': 1725, 'reason': 'end-of-route'}), ('control 51', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 18, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 1100, 'reason': '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: length cap from the front	`{'eoa_m': 600, 'reason': 'max-length'}`	`{'eoa_m': 1000, 'reason': 'max-length'}`	Failed
regression: cap exactly at the obstacle	`{'eoa_m': 600, 'reason': 'max-length'}`	`{'eoa_m': 975, 'reason': 'occupied'}`	Failed
sampled regression 12	`{'eoa_m': 850, 'reason': 'max-length'}`	`{'eoa_m': 884, 'reason': 'max-length'}`	Failed
boundary: own section occupied	`{'eoa_m': 675, 'reason': 'end-of-route'}`	`{'eoa_m': 675, 'reason': 'end-of-route'}`	Passed
boundary: occupied section two ahead	`{'eoa_m': 375, 'reason': 'occupied'}`	`{'eoa_m': 375, 'reason': 'occupied'}`	Passed
control 1	`{'eoa_m': 150, 'reason': 'unlocked'}`	`{'eoa_m': 150, 'reason': 'unlocked'}`	Passed
control 4	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	Passed
control 7	`{'eoa_m': 550, 'reason': 'unlocked'}`	`{'eoa_m': 550, 'reason': 'unlocked'}`	Passed

SHA-256 / 4a889a4aa4181cb4588cf8cb27800f931f7f5a175fd0fab00264c327915e84c0

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(x):
    secs = x['sections']
    bounds = []
    acc = 0
    for s in secs:
        bounds.append(acc)
        acc += s['len']
    k = x['train_sec']
    eoa = acc
    reason = 'end-of-route'
    for j in range(k + 1, len(secs)):
        if secs[j]['state'] != 'locked':
            eoa = bounds[j]
            reason = secs[j]['state']
            break
    front = bounds[k] + x['offset_m']
    if eoa - front >= x['max_ma_m']:
        eoa = front + x['max_ma_m']
        reason = 'max-length'
    if reason != 'max-length':
        eoa -= x['margin_m']
    return {'eoa_m': eoa, 'reason': reason}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 1', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 69, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'unlocked'}), ('control 4', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 206, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 1325, 'reason': 'end-of-route'}), ('control 7', {'sections': [{'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 500, 'state': 'unlocked'}, {'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 108, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 550, 'reason': 'unlocked'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('control 15', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 4, 'offset_m': 137, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 2100, 'reason': 'end-of-route'}), ('control 18', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 3, 'offset_m': 181, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 1250, 'reason': 'occupied'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 70', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 212, 'max_ma_m': 300, 'margin_m': 0}, {'eoa_m': 512, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('control 23', {'sections': [{'len': 350, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 1100, 'reason': 'unlocked'}), ('sampled regression 26', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 9, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 409, 'reason': 'max-length'}), ('sampled regression 29', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 288, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 1000, 'reason': 'occupied'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 34', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 222, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 850, 'reason': 'unlocked'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('control 40', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 500, 'state': 'unlocked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 25, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 500, 'reason': 'unlocked'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('sampled regression 45', {'sections': [{'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 348, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 1198, 'reason': 'max-length'}), ('sampled regression 48', {'sections': [{'len': 500, 'state': 'unlocked'}, {'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 200, 'max_ma_m': 1000, 'margin_m': 25}, {'eoa_m': 1725, 'reason': 'end-of-route'}), ('control 51', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 18, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 1100, 'reason': '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: length cap from the front	`{'eoa_m': 1000, 'reason': 'max-length'}`	`{'eoa_m': 1000, 'reason': 'max-length'}`	Passed
regression: cap exactly at the obstacle	`{'eoa_m': 1000, 'reason': 'max-length'}`	`{'eoa_m': 975, 'reason': 'occupied'}`	Failed
sampled regression 12	`{'eoa_m': 884, 'reason': 'max-length'}`	`{'eoa_m': 884, 'reason': 'max-length'}`	Passed
boundary: own section occupied	`{'eoa_m': 675, 'reason': 'end-of-route'}`	`{'eoa_m': 675, 'reason': 'end-of-route'}`	Passed
boundary: occupied section two ahead	`{'eoa_m': 375, 'reason': 'occupied'}`	`{'eoa_m': 375, 'reason': 'occupied'}`	Passed
control 1	`{'eoa_m': 150, 'reason': 'unlocked'}`	`{'eoa_m': 150, 'reason': 'unlocked'}`	Passed
control 4	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	Passed
control 7	`{'eoa_m': 550, 'reason': 'unlocked'}`	`{'eoa_m': 550, 'reason': 'unlocked'}`	Passed

SHA-256 / fa13977b26fdb0f97def3aa38e2c4d048d5fa1bb65632d72c47bf95e3ee56af6

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(x):
    secs = x['sections']
    bounds = []
    acc = 0
    for s in secs:
        bounds.append(acc)
        acc += s['len']
    k = x['train_sec']
    eoa = acc
    reason = 'end-of-route'
    for j in range(k + 1, len(secs)):
        if secs[j]['state'] != 'locked':
            eoa = bounds[j]
            reason = secs[j]['state']
            break
    front = bounds[k] + x['offset_m']
    if eoa - front > x['max_ma_m']:
        eoa = front + x['max_ma_m']
        reason = 'max-length'
    if reason != 'max-length':
        eoa -= x['margin_m']
    return {'eoa_m': eoa, 'reason': reason}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 1', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 69, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'unlocked'}), ('control 4', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 206, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 1325, 'reason': 'end-of-route'}), ('control 7', {'sections': [{'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 500, 'state': 'unlocked'}, {'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 108, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 550, 'reason': 'unlocked'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('control 15', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 4, 'offset_m': 137, 'max_ma_m': 5000, 'margin_m': 0}, {'eoa_m': 2100, 'reason': 'end-of-route'}), ('control 18', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 3, 'offset_m': 181, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 1250, 'reason': 'occupied'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 70', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 212, 'max_ma_m': 300, 'margin_m': 0}, {'eoa_m': 512, 'reason': 'max-length'}), ('boundary: end of route with margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 0, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 150, 'reason': 'end-of-route'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('control 23', {'sections': [{'len': 350, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 50}, {'eoa_m': 1100, 'reason': 'unlocked'}), ('sampled regression 26', {'sections': [{'len': 100, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 9, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 409, 'reason': 'max-length'}), ('sampled regression 29', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 288, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 1000, 'reason': 'occupied'})], [('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 12', {'sections': [{'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}, {'len': 200, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 34, 'max_ma_m': 300, 'margin_m': 50}, {'eoa_m': 884, 'reason': 'max-length'}), ('boundary: unlocked section margin', {'sections': [{'len': 100, 'state': 'occupied'}, {'len': 150, 'state': 'locked'}, {'len': 100, 'state': 'unlocked'}], 'train_sec': 0, 'offset_m': 20, 'max_ma_m': 5000, 'margin_m': 30}, {'eoa_m': 220, 'reason': 'unlocked'}), ('boundary: own section occupied', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 50, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 675, 'reason': 'end-of-route'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('control 34', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 222, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 850, 'reason': 'unlocked'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('control 40', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 500, 'state': 'unlocked'}, {'len': 100, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 25, 'max_ma_m': 1000, 'margin_m': 0}, {'eoa_m': 500, 'reason': 'unlocked'})], [('regression: length cap from the front', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 1000, 'reason': 'max-length'}), ('regression: cap exactly at the obstacle', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 500, 'state': 'occupied'}], 'train_sec': 0, 'offset_m': 400, 'max_ma_m': 600, 'margin_m': 25}, {'eoa_m': 975, 'reason': 'occupied'}), ('sampled regression 37', {'sections': [{'len': 500, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 200, 'state': 'unlocked'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 2, 'max_ma_m': 600, 'margin_m': 50}, {'eoa_m': 602, 'reason': 'max-length'}), ('boundary: occupied section two ahead', {'sections': [{'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}, {'len': 300, 'state': 'occupied'}, {'len': 100, 'state': 'locked'}], 'train_sec': 0, 'offset_m': 100, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'occupied'}), ('boundary: unlocked section next', {'sections': [{'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 300, 'state': 'unlocked'}], 'train_sec': 1, 'offset_m': 10, 'max_ma_m': 5000, 'margin_m': 25}, {'eoa_m': 375, 'reason': 'unlocked'}), ('sampled regression 45', {'sections': [{'len': 350, 'state': 'unlocked'}, {'len': 200, 'state': 'locked'}, {'len': 350, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}, {'len': 200, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 348, 'max_ma_m': 300, 'margin_m': 25}, {'eoa_m': 1198, 'reason': 'max-length'}), ('sampled regression 48', {'sections': [{'len': 500, 'state': 'unlocked'}, {'len': 200, 'state': 'unlocked'}, {'len': 350, 'state': 'occupied'}, {'len': 350, 'state': 'locked'}, {'len': 350, 'state': 'locked'}], 'train_sec': 2, 'offset_m': 200, 'max_ma_m': 1000, 'margin_m': 25}, {'eoa_m': 1725, 'reason': 'end-of-route'}), ('control 51', {'sections': [{'len': 500, 'state': 'locked'}, {'len': 100, 'state': 'occupied'}, {'len': 500, 'state': 'locked'}, {'len': 200, 'state': 'occupied'}, {'len': 200, 'state': 'locked'}], 'train_sec': 1, 'offset_m': 18, 'max_ma_m': 600, 'margin_m': 0}, {'eoa_m': 1100, 'reason': '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: length cap from the front	`{'eoa_m': 1000, 'reason': 'max-length'}`	`{'eoa_m': 1000, 'reason': 'max-length'}`	Passed
regression: cap exactly at the obstacle	`{'eoa_m': 975, 'reason': 'occupied'}`	`{'eoa_m': 975, 'reason': 'occupied'}`	Passed
sampled regression 12	`{'eoa_m': 884, 'reason': 'max-length'}`	`{'eoa_m': 884, 'reason': 'max-length'}`	Passed
boundary: own section occupied	`{'eoa_m': 675, 'reason': 'end-of-route'}`	`{'eoa_m': 675, 'reason': 'end-of-route'}`	Passed
boundary: occupied section two ahead	`{'eoa_m': 375, 'reason': 'occupied'}`	`{'eoa_m': 375, 'reason': 'occupied'}`	Passed
control 1	`{'eoa_m': 150, 'reason': 'unlocked'}`	`{'eoa_m': 150, 'reason': 'unlocked'}`	Passed
control 4	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	`{'eoa_m': 1325, 'reason': 'end-of-route'}`	Passed
control 7	`{'eoa_m': 550, 'reason': 'unlocked'}`	`{'eoa_m': 550, 'reason': 'unlocked'}`	Passed

SHA-256 / e8399bcfdc08ddd71dce7dfb41b0d5009fed172c0ee99d6b893ad1d113584018

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 2026-09-29T14:47:49.779956+00:00.

Case digest / 0cd6e13297fce33425932e2daaaf8e4999bf8f5c0a581088230dec5170390ae9