FAILURE MAP
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FA-92931 / EV charging session scheduling / Open access

Shared circuit current allocation: leftover recipients · case 01

Paused vehicles receive a 1 A setpoint, below the minimum pilot current.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Leftover amps are handed out over all EVs instead of the admitted ones.

THE FAILURE

Leftover amps are handed out over all EVs instead of the admitted ones.

Unsuccessful approach: Iterating admitted EVs by id instead of admission order favors the wrong vehicle.

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 -= e[1]
            open_.remove(e)
    for e in evs:
        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: leftover recipients',
   [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: leftover recipients (partial repair)',
   [30,
    [['EV5', 24, 2], ['EV2', 32, 3], ['EV0', 5, 1], ['EV1', 5, 2], ['EV4', 24, 3], ['EV3', 16, 2]]],
   [['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 7], ['EV4', 8], ['EV5', 7]]],
  ['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: leftover recipients',
   [32,
    [['EV2', 32, 1], ['EV4', 32, 0], ['EV3', 6, 2], ['EV1', 32, 2], ['EV5', 24, 1],
     ['EV0', 32, 3]]],
   [['EV0', 7], ['EV1', 7], ['EV2', 6], ['EV3', 6], ['EV4', 0], ['EV5', 6]]],
  ['regression: leftover recipients (partial repair)',
   [63,
    [['EV2', 16, 0], ['EV1', 24, 2], ['EV0', 6, 1], ['EV5', 6, 1], ['EV3', 32, 3], ['EV4', 16, 1]]],
   [['EV0', 6], ['EV1', 13], ['EV2', 12], ['EV3', 13], ['EV4', 13], ['EV5', 6]]],
  ['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: leftover recipients',
   [48, [['EV1', 16, 2], ['EV0', 16, 2], ['EV4', 32, 3], ['EV2', 24, 3], ['EV3', 24, 3]]],
   [['EV0', 9], ['EV1', 9], ['EV2', 10], ['EV3', 10], ['EV4', 10]]],
  ['regression: leftover recipients (partial repair)',
   [32, [['EV0', 32, 0], ['EV2', 24, 0], ['EV3', 10, 1], ['EV4', 6, 1], ['EV1', 5, 3]]],
   [['EV0', 9], ['EV1', 0], ['EV2', 8], ['EV3', 9], ['EV4', 6]]],
  ['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: leftover recipients', [48, [['EV2', 8, 2], ['EV0', 32, 3], ['EV1', 5, 3]]],
   [['EV0', 32], ['EV1', 0], ['EV2', 8]]],
  ['regression: leftover recipients (partial repair)',
   [48, [['EV3', 16, 3], ['EV2', 6, 0], ['EV4', 16, 0], ['EV1', 16, 2], ['EV0', 32, 2]]],
   [['EV0', 11], ['EV1', 10], ['EV2', 6], ['EV3', 11], ['EV4', 10]]],
  ['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: leftover recipients',
   [32, [['EV1', 10, 3], ['EV2', 5, 1], ['EV3', 10, 0], ['EV0', 8, 2]]],
   [['EV0', 8], ['EV1', 10], ['EV2', 0], ['EV3', 10]]],
  ['regression: leftover recipients (partial repair)',
   [63, [['EV0', 16, 3], ['EV4', 16, 3], ['EV1', 32, 1], ['EV3', 24, 2], ['EV2', 16, 0]]],
   [['EV0', 13], ['EV1', 12], ['EV2', 12], ['EV3', 13], ['EV4', 13]]],
  ['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 fixtureActualExpectedOutcome
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: leftover recipients[['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 1], ['EV4', 24], ['EV5', 8]][['EV0', 24], ['EV1', 0], ['EV2', 6], ['EV3', 0], ['EV4', 24], ['EV5', 8]]Failed
regression: leftover recipients (partial repair)[['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 7], ['EV4', 7], ['EV5', 8]][['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 7], ['EV4', 8], ['EV5', 7]]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 / 2b721fd411c3d7d045b373da42f03001f72ce93d9650b02c1d00fd9c7c2cae81

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 -= e[1]
            open_.remove(e)
    for e in sorted(admitted, key=lambda e: e[0]):
        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: leftover recipients',
   [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: leftover recipients (partial repair)',
   [30,
    [['EV5', 24, 2], ['EV2', 32, 3], ['EV0', 5, 1], ['EV1', 5, 2], ['EV4', 24, 3], ['EV3', 16, 2]]],
   [['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 7], ['EV4', 8], ['EV5', 7]]],
  ['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: leftover recipients',
   [32,
    [['EV2', 32, 1], ['EV4', 32, 0], ['EV3', 6, 2], ['EV1', 32, 2], ['EV5', 24, 1],
     ['EV0', 32, 3]]],
   [['EV0', 7], ['EV1', 7], ['EV2', 6], ['EV3', 6], ['EV4', 0], ['EV5', 6]]],
  ['regression: leftover recipients (partial repair)',
   [63,
    [['EV2', 16, 0], ['EV1', 24, 2], ['EV0', 6, 1], ['EV5', 6, 1], ['EV3', 32, 3], ['EV4', 16, 1]]],
   [['EV0', 6], ['EV1', 13], ['EV2', 12], ['EV3', 13], ['EV4', 13], ['EV5', 6]]],
  ['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: leftover recipients',
   [48, [['EV1', 16, 2], ['EV0', 16, 2], ['EV4', 32, 3], ['EV2', 24, 3], ['EV3', 24, 3]]],
   [['EV0', 9], ['EV1', 9], ['EV2', 10], ['EV3', 10], ['EV4', 10]]],
  ['regression: leftover recipients (partial repair)',
   [32, [['EV0', 32, 0], ['EV2', 24, 0], ['EV3', 10, 1], ['EV4', 6, 1], ['EV1', 5, 3]]],
   [['EV0', 9], ['EV1', 0], ['EV2', 8], ['EV3', 9], ['EV4', 6]]],
  ['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: leftover recipients', [48, [['EV2', 8, 2], ['EV0', 32, 3], ['EV1', 5, 3]]],
   [['EV0', 32], ['EV1', 0], ['EV2', 8]]],
  ['regression: leftover recipients (partial repair)',
   [48, [['EV3', 16, 3], ['EV2', 6, 0], ['EV4', 16, 0], ['EV1', 16, 2], ['EV0', 32, 2]]],
   [['EV0', 11], ['EV1', 10], ['EV2', 6], ['EV3', 11], ['EV4', 10]]],
  ['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: leftover recipients',
   [32, [['EV1', 10, 3], ['EV2', 5, 1], ['EV3', 10, 0], ['EV0', 8, 2]]],
   [['EV0', 8], ['EV1', 10], ['EV2', 0], ['EV3', 10]]],
  ['regression: leftover recipients (partial repair)',
   [63, [['EV0', 16, 3], ['EV4', 16, 3], ['EV1', 32, 1], ['EV3', 24, 2], ['EV2', 16, 0]]],
   [['EV0', 13], ['EV1', 12], ['EV2', 12], ['EV3', 13], ['EV4', 13]]],
  ['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 fixtureActualExpectedOutcome
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: leftover recipients[['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: leftover recipients (partial repair)[['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 8], ['EV4', 7], ['EV5', 7]][['EV0', 0], ['EV1', 0], ['EV2', 8], ['EV3', 7], ['EV4', 8], ['EV5', 7]]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 / 5c6dcd1423ddea16a2df9ca5dc14ffc25290d63310252b90a234dafd91864658

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.

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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 2026-09-29T14:51:50.454881+00:00.

Case digest / 50f3c2b269e52fa2ab3b3c2cac45a0734efab5c4ebde61d0bd6c0de9a03f8e5f