FA-92921 / EV charging session scheduling / Open access
Shared circuit current allocation: capped vehicle surplus return · case 01
Amps released by vehicles with low onboard limits are not given to other vehicles.
ROOT CAUSE
A capped vehicle is charged the full equal share against the remaining budget instead of its actual max.
THE FAILURE
A capped vehicle is charged the full equal share against the remaining budget instead of its actual max.
Unsuccessful approach: Subtracting only the 6 A minimum over-credits the budget and oversubscribes the circuit.
Case contract
evs is a list of [id, max_a, priority]. An EV with max_a < 6 cannot be served. Eligible EVs are ordered by priority descending then id; each is admitted while 6*(admitted+1) <= limit_a. Admitted EVs are water-filled: repeatedly give floor(remaining/open) amps, fixing EVs whose max_a <= share at their max. Leftover amps go one each in admission order to EVs below max. Return [[id, amps]] for every EV sorted by id (0 = paused).
Why this case matters
Depot, workplace and public EV chargers schedule sessions against prices, circuit limits and departure deadlines; a wrong decision silently strands a driver or overloads a feeder.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(limit_a, evs):
elig = [e for e in evs if e[1] >= 6]
elig.sort(key=lambda e: (-e[2], e[0]))
admitted = []
for e in elig:
if 6 * (len(admitted) + 1) <= limit_a:
admitted.append(e)
alloc = {e[0]: 0 for e in evs}
remaining = limit_a
open_ = list(admitted)
while open_:
share = remaining // len(open_)
capped = [e for e in open_ if e[1] <= share]
if not capped:
for e in open_:
alloc[e[0]] = share
remaining -= share * len(open_)
break
for e in capped:
alloc[e[0]] = e[1]
remaining -= share
open_.remove(e)
for e in admitted:
if remaining <= 0:
break
if alloc[e[0]] < e[1]:
alloc[e[0]] += 1
remaining -= 1
return [[k, alloc[k]] for k in sorted(alloc)]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[63,
[['EV4', 24, 3], ['EV5', 8, 1], ['EV2', 6, 0], ['EV3', 5, 1], ['EV1', 5, 3], ['EV0', 24, 3]]],
[['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]]],
['regression: capped vehicle surplus return (partial repair)',
[30, [['EV0', 8, 0], ['EV1', 16, 3], ['EV2', 32, 0]]], [['EV0', 8], ['EV1', 11], ['EV2', 11]]],
['control 1', [32, [['EV0', 32, 3], ['EV1', 24, 3]]], [['EV0', 16], ['EV1', 16]]],
['control 2', [24, [['EV0', 16, 2], ['EV1', 32, 2], ['EV2', 32, 0], ['EV3', 8, 1]]],
[['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[16, [['EV0', 10, 0], ['EV3', 16, 2], ['EV1', 6, 2], ['EV2', 5, 1]]],
[['EV0', 0], ['EV1', 6], ['EV2', 0], ['EV3', 10]]],
['regression: capped vehicle surplus return (partial repair)',
[40, [['EV0', 16, 0], ['EV2', 16, 2], ['EV3', 8, 2], ['EV1', 6, 1]]],
[['EV0', 13], ['EV1', 6], ['EV2', 13], ['EV3', 8]]],
['control 1',
[30,
[['EV1', 8, 3], ['EV4', 6, 2], ['EV0', 16, 0], ['EV2', 10, 3], ['EV3', 24, 1], ['EV5', 6, 2]]],
[['EV0', 0], ['EV1', 6], ['EV2', 6], ['EV3', 6], ['EV4', 6], ['EV5', 6]]],
['control 2', [40, [['EV1', 5, 1], ['EV0', 32, 2]]], [['EV0', 32], ['EV1', 0]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[16, [['EV0', 6, 1], ['EV2', 5, 1], ['EV1', 24, 3]]], [['EV0', 6], ['EV1', 10], ['EV2', 0]]],
['regression: capped vehicle surplus return (partial repair)',
[40, [['EV1', 16, 0], ['EV2', 10, 2], ['EV3', 10, 3], ['EV4', 8, 1], ['EV0', 24, 1]]],
[['EV0', 8], ['EV1', 8], ['EV2', 8], ['EV3', 8], ['EV4', 8]]],
['control 1', [18, [['EV2', 32, 0], ['EV0', 5, 2], ['EV1', 24, 3]]],
[['EV0', 0], ['EV1', 9], ['EV2', 9]]],
['control 2', [16, [['EV0', 24, 3], ['EV1', 16, 0], ['EV2', 16, 2]]],
[['EV0', 8], ['EV1', 0], ['EV2', 8]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[48, [['EV2', 8, 2], ['EV0', 32, 3], ['EV1', 5, 3]]], [['EV0', 32], ['EV1', 0], ['EV2', 8]]],
['regression: capped vehicle surplus return (partial repair)',
[32, [['EV1', 8, 1], ['EV2', 32, 0], ['EV0', 32, 1]]], [['EV0', 12], ['EV1', 8], ['EV2', 12]]],
['control 1', [16, [['EV1', 16, 2], ['EV0', 32, 3]]], [['EV0', 8], ['EV1', 8]]],
['control 2',
[48,
[['EV3', 8, 0], ['EV1', 16, 0], ['EV4', 5, 0], ['EV2', 8, 0], ['EV5', 10, 0], ['EV0', 10, 3]]],
[['EV0', 10], ['EV1', 12], ['EV2', 8], ['EV3', 8], ['EV4', 0], ['EV5', 10]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[40, [['EV1', 24, 3], ['EV0', 6, 0], ['EV2', 32, 1], ['EV3', 32, 3]]],
[['EV0', 6], ['EV1', 12], ['EV2', 11], ['EV3', 11]]],
['regression: capped vehicle surplus return (partial repair)',
[40,
[['EV0', 5, 0], ['EV2', 24, 3], ['EV1', 32, 0], ['EV5', 8, 2], ['EV3', 10, 2], ['EV4', 8, 1]]],
[['EV0', 0], ['EV1', 8], ['EV2', 8], ['EV3', 8], ['EV4', 8], ['EV5', 8]]],
['control 1', [40, [['EV2', 5, 0], ['EV0', 6, 2], ['EV3', 24, 2], ['EV1', 10, 3]]],
[['EV0', 6], ['EV1', 10], ['EV2', 0], ['EV3', 24]]],
['control 2', [10, [['EV0', 10, 0]]], [['EV0', 10]]]]]
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 |
|---|---|---|---|
| boundary: exactly one minimum share | [['A', 6], ['B', 0]] | [['A', 6], ['B', 0]] | Passed |
| boundary: EV at 6 A maximum | [['A', 6], ['B', 10]] | [['A', 6], ['B', 14]] | Failed |
| boundary: no EVs | [] | [] | Passed |
| regression: capped vehicle surplus return | [['EV0', 17], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 16], ['EV5', 8]] | [['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]] | Failed |
| regression: capped vehicle surplus return (partial repair) | [['EV0', 8], ['EV1', 10], ['EV2', 10]] | [['EV0', 8], ['EV1', 11], ['EV2', 11]] | Failed |
| control 1 | [['EV0', 16], ['EV1', 16]] | [['EV0', 16], ['EV1', 16]] | Passed |
| control 2 | [['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]] | [['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]] | Passed |
SHA-256 / 3300630c09591a99befcc8cc6b49ddeea73686d84932791ce67f1a1f41d928d3
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(limit_a, evs):
elig = [e for e in evs if e[1] >= 6]
elig.sort(key=lambda e: (-e[2], e[0]))
admitted = []
for e in elig:
if 6 * (len(admitted) + 1) <= limit_a:
admitted.append(e)
alloc = {e[0]: 0 for e in evs}
remaining = limit_a
open_ = list(admitted)
while open_:
share = remaining // len(open_)
capped = [e for e in open_ if e[1] <= share]
if not capped:
for e in open_:
alloc[e[0]] = share
remaining -= share * len(open_)
break
for e in capped:
alloc[e[0]] = e[1]
remaining -= 6
open_.remove(e)
for e in admitted:
if remaining <= 0:
break
if alloc[e[0]] < e[1]:
alloc[e[0]] += 1
remaining -= 1
return [[k, alloc[k]] for k in sorted(alloc)]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[63,
[['EV4', 24, 3], ['EV5', 8, 1], ['EV2', 6, 0], ['EV3', 5, 1], ['EV1', 5, 3], ['EV0', 24, 3]]],
[['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]]],
['regression: capped vehicle surplus return (partial repair)',
[30, [['EV0', 8, 0], ['EV1', 16, 3], ['EV2', 32, 0]]], [['EV0', 8], ['EV1', 11], ['EV2', 11]]],
['control 1', [32, [['EV0', 32, 3], ['EV1', 24, 3]]], [['EV0', 16], ['EV1', 16]]],
['control 2', [24, [['EV0', 16, 2], ['EV1', 32, 2], ['EV2', 32, 0], ['EV3', 8, 1]]],
[['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[16, [['EV0', 10, 0], ['EV3', 16, 2], ['EV1', 6, 2], ['EV2', 5, 1]]],
[['EV0', 0], ['EV1', 6], ['EV2', 0], ['EV3', 10]]],
['regression: capped vehicle surplus return (partial repair)',
[40, [['EV0', 16, 0], ['EV2', 16, 2], ['EV3', 8, 2], ['EV1', 6, 1]]],
[['EV0', 13], ['EV1', 6], ['EV2', 13], ['EV3', 8]]],
['control 1',
[30,
[['EV1', 8, 3], ['EV4', 6, 2], ['EV0', 16, 0], ['EV2', 10, 3], ['EV3', 24, 1], ['EV5', 6, 2]]],
[['EV0', 0], ['EV1', 6], ['EV2', 6], ['EV3', 6], ['EV4', 6], ['EV5', 6]]],
['control 2', [40, [['EV1', 5, 1], ['EV0', 32, 2]]], [['EV0', 32], ['EV1', 0]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[16, [['EV0', 6, 1], ['EV2', 5, 1], ['EV1', 24, 3]]], [['EV0', 6], ['EV1', 10], ['EV2', 0]]],
['regression: capped vehicle surplus return (partial repair)',
[40, [['EV1', 16, 0], ['EV2', 10, 2], ['EV3', 10, 3], ['EV4', 8, 1], ['EV0', 24, 1]]],
[['EV0', 8], ['EV1', 8], ['EV2', 8], ['EV3', 8], ['EV4', 8]]],
['control 1', [18, [['EV2', 32, 0], ['EV0', 5, 2], ['EV1', 24, 3]]],
[['EV0', 0], ['EV1', 9], ['EV2', 9]]],
['control 2', [16, [['EV0', 24, 3], ['EV1', 16, 0], ['EV2', 16, 2]]],
[['EV0', 8], ['EV1', 0], ['EV2', 8]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[48, [['EV2', 8, 2], ['EV0', 32, 3], ['EV1', 5, 3]]], [['EV0', 32], ['EV1', 0], ['EV2', 8]]],
['regression: capped vehicle surplus return (partial repair)',
[32, [['EV1', 8, 1], ['EV2', 32, 0], ['EV0', 32, 1]]], [['EV0', 12], ['EV1', 8], ['EV2', 12]]],
['control 1', [16, [['EV1', 16, 2], ['EV0', 32, 3]]], [['EV0', 8], ['EV1', 8]]],
['control 2',
[48,
[['EV3', 8, 0], ['EV1', 16, 0], ['EV4', 5, 0], ['EV2', 8, 0], ['EV5', 10, 0], ['EV0', 10, 3]]],
[['EV0', 10], ['EV1', 12], ['EV2', 8], ['EV3', 8], ['EV4', 0], ['EV5', 10]]]],
[['boundary: exactly one minimum share', [6, [['A', 32, 0], ['B', 32, 0]]], [['A', 6], ['B', 0]]],
['boundary: EV at 6 A maximum', [20, [['A', 6, 0], ['B', 32, 0]]], [['A', 6], ['B', 14]]],
['boundary: no EVs', [32, []], []],
['regression: capped vehicle surplus return',
[40, [['EV1', 24, 3], ['EV0', 6, 0], ['EV2', 32, 1], ['EV3', 32, 3]]],
[['EV0', 6], ['EV1', 12], ['EV2', 11], ['EV3', 11]]],
['regression: capped vehicle surplus return (partial repair)',
[40,
[['EV0', 5, 0], ['EV2', 24, 3], ['EV1', 32, 0], ['EV5', 8, 2], ['EV3', 10, 2], ['EV4', 8, 1]]],
[['EV0', 0], ['EV1', 8], ['EV2', 8], ['EV3', 8], ['EV4', 8], ['EV5', 8]]],
['control 1', [40, [['EV2', 5, 0], ['EV0', 6, 2], ['EV3', 24, 2], ['EV1', 10, 3]]],
[['EV0', 6], ['EV1', 10], ['EV2', 0], ['EV3', 24]]],
['control 2', [10, [['EV0', 10, 0]]], [['EV0', 10]]]]]
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 |
|---|---|---|---|
| boundary: exactly one minimum share | [['A', 6], ['B', 0]] | [['A', 6], ['B', 0]] | Passed |
| boundary: EV at 6 A maximum | [['A', 6], ['B', 14]] | [['A', 6], ['B', 14]] | Passed |
| boundary: no EVs | [] | [] | Passed |
| regression: capped vehicle surplus return | [['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]] | [['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]] | Passed |
| regression: capped vehicle surplus return (partial repair) | [['EV0', 8], ['EV1', 12], ['EV2', 12]] | [['EV0', 8], ['EV1', 11], ['EV2', 11]] | Failed |
| control 1 | [['EV0', 16], ['EV1', 16]] | [['EV0', 16], ['EV1', 16]] | Passed |
| control 2 | [['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]] | [['EV0', 6], ['EV1', 6], ['EV2', 6], ['EV3', 6]] | Passed |
SHA-256 / 8f42b714cc4b1947a4f2b5fd818539e6782b804bb2fa633b908af05d7aee9402
HELD IN THE MEMBER ARCHIVE
The verified repair and its recorded checks are member-only.
This mechanism has 7 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.
Sign in to the archive ↗Verification & scope
Deterministic stipulated toy contract for teaching; no claim of conformance with any standard, vendor protocol or production controller. 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 2026-09-29T14:51:50.397930+00:00.
Case digest / f14a7217810d9336a02ac6b26a00383c9b58259ef059e01481bc911989fc28a1