FA-58166 / Double-entry ledger accounting / Open access
Cost pool allocation entry: magnitude for shares · case 01
Reversal allocations produce negative or lopsided center shares.
ROOT CAUSE
Shares are floored from the signed amount, so negative amounts floor away from zero.
VERIFIED REPAIR
Allocate the magnitude and express direction through the sides.
Unsuccessful approach: Changing only the floor still mixes a signed base with unsigned remainders.
Case contract
x = {'amount': signed cents, 'weights': [[center, non-negative weight]] (some positive), 'source': account}. The pool magnitude is split across positive-weight centers by the largest remainder method: floor shares, then one extra cent to the largest remainders, ties to the earlier-listed center. A non-negative amount credits the source and debits centers; a negative amount (reversal) debits the source and credits centers, all amounts positive. Return lines [[source, side, magnitude]] + [[center, side, share]] for nonzero shares in listing order.
Why this case matters
Ledger software must keep debits equal to credits and apply normal-balance, period and cutoff rules exactly; small sign or boundary slips silently misstate financial statements.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
amt = x['amount']
side_src, side_dst = ('C', 'D') if amt >= 0 else ('D', 'C')
mag = abs(amt)
ws = [(c, w) for c, w in x['weights'] if w > 0]
total = sum(w for _, w in ws)
base = [amt * w // total for _, w in ws]
rems = [amt * w % total for _, w in ws]
left = amt - sum(base)
order = sorted(range(len(ws)), key=lambda i: (-rems[i], i))
for i in order[:left]:
base[i] += 1
lines = [[x['source'], side_src, mag]]
for (c, w), share in zip(ws, base):
if share:
lines.append([c, side_dst, share])
return lines
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: magnitude for shares', {'amount': -7, 'weights': [['ops', 0], ['mkt', 5], ['hr', 1], ['it', 2], ['lab', 0]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]]], ['control 1', {'amount': 7, 'weights': [['fin', 0], ['it', 7], ['hr', 2], ['lab', 3], ['ops', 2]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]]], ['control 2', {'amount': 7, 'weights': [['mkt', 0], ['fin', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 7]]], ['control 3', {'amount': 99999, 'weights': [['hr', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 99999], ['hr', 'D', 99999]]], ['control 4', {'amount': 0, 'weights': [['ops', 3], ['mkt', 7], ['fin', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 5', {'amount': 100, 'weights': [['ops', 5], ['it', 5]], 'source': 'pool'}, [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]]], ['control 6', {'amount': 0, 'weights': [['ops', 5], ['hr', 5], ['mkt', 7], ['fin', 3]], 'source': 'pool'}, [['pool', 'C', 0]]]], [['regression: magnitude for shares', {'amount': -101, 'weights': [['lab', 1], ['mkt', 5], ['ops', 2]], 'source': 'pool'}, [['pool', 'D', 101], ['lab', 'C', 13], ['mkt', 'C', 63], ['ops', 'C', 25]]], ['control 1', {'amount': 7, 'weights': [['mkt', 0], ['it', 7], ['ops', 2], ['fin', 2], ['lab', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['ops', 'D', 1], ['fin', 'D', 1], ['lab', 'D', 1]]], ['control 2', {'amount': 0, 'weights': [['it', 3], ['lab', 1], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 3', {'amount': 101, 'weights': [['lab', 7], ['hr', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['lab', 'D', 59], ['hr', 'D', 42]]], ['control 4', {'amount': 10, 'weights': [['lab', 1], ['it', 3], ['hr', 1], ['ops', 7], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 2], ['hr', 'D', 1], ['ops', 'D', 6]]], ['control 5', {'amount': 10, 'weights': [['mkt', 1], ['it', 2], ['fin', 1], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 2], ['fin', 'D', 1], ['hr', 'D', 6]]], ['control 6', {'amount': 1000, 'weights': [['mkt', 2], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 1000], ['mkt', 'D', 286], ['fin', 'D', 714]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['mkt', 7], ['fin', 7]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['fin', 'C', 3]]], ['control 1', {'amount': 7, 'weights': [['fin', 1], ['mkt', 5]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 1], ['mkt', 'D', 6]]], ['control 2', {'amount': 7, 'weights': [['it', 0], ['lab', 7], ['mkt', 1], ['hr', 3]], 'source': 'pool'}, [['pool', 'C', 7], ['lab', 'D', 4], ['mkt', 'D', 1], ['hr', 'D', 2]]], ['control 3', {'amount': 3, 'weights': [['it', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 3]]], ['control 4', {'amount': 10, 'weights': [['ops', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['lab', 'D', 6]]], ['control 5', {'amount': 1000, 'weights': [['ops', 7], ['mkt', 5], ['fin', 7]], 'source': 'pool'}, [['pool', 'C', 1000], ['ops', 'D', 369], ['mkt', 'D', 263], ['fin', 'D', 368]]], ['control 6', {'amount': 10, 'weights': [['ops', 1], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 2], ['lab', 'D', 8]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['lab', 2], ['ops', 7], ['mkt', 2]], 'source': 'pool'}, [['pool', 'D', 7], ['lab', 'C', 1], ['ops', 'C', 5], ['mkt', 'C', 1]]], ['control 1', {'amount': 100, 'weights': [['it', 7], ['fin', 3], ['mkt', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 100], ['it', 'D', 39], ['fin', 'D', 17], ['mkt', 'D', 39], ['hr', 'D', 5]]], ['control 2', {'amount': 10, 'weights': [['lab', 2], ['it', 5], ['hr', 7], ['mkt', 0], ['ops', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 3], ['hr', 'D', 3], ['ops', 'D', 3]]], ['control 3', {'amount': 1000, 'weights': [['fin', 7], ['mkt', 3], ['it', 3], ['lab', 1], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 1000], ['fin', 'D', 438], ['mkt', 'D', 188], ['it', 'D', 187], ['lab', 'D', 62], ['hr', 'D', 125]]], ['control 4', {'amount': 3, 'weights': [['it', 3], ['lab', 3], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 1], ['lab', 'D', 1], ['hr', 'D', 1]]], ['control 5', {'amount': 99999, 'weights': [['hr', 0], ['lab', 0], ['ops', 3], ['mkt', 5], ['it', 2]], 'source': 'pool'}, [['pool', 'C', 99999], ['ops', 'D', 30000], ['mkt', 'D', 49999], ['it', 'D', 20000]]], ['control 6', {'amount': 101, 'weights': [['mkt', 3], ['hr', 0], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['mkt', 'D', 38], ['fin', 'D', 63]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['fin', 3], ['mkt', 1]], 'source': 'pool'}, [['pool', 'D', 7], ['fin', 'C', 5], ['mkt', 'C', 2]]], ['control 1', {'amount': 100, 'weights': [['fin', 2], ['hr', 0], ['it', 0], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 100], ['fin', 'D', 100]]], ['control 2', {'amount': 10, 'weights': [['ops', 3], ['it', 1], ['mkt', 3], ['hr', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['it', 'D', 2], ['mkt', 'D', 4]]], ['control 3', {'amount': 7, 'weights': [['mkt', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 7], ['mkt', 'D', 7]]], ['control 4', {'amount': 10, 'weights': [['mkt', 1], ['it', 7], ['fin', 0], ['ops', 1]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 8], ['ops', 'D', 1]]], ['control 5', {'amount': 101, 'weights': [['fin', 5], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 72], ['hr', 'D', 29]]], ['control 6', {'amount': 101, 'weights': [['fin', 2], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 51], ['hr', 'D', 50]]]]]
for label, args, expected in fixtures[N-1]:
try:
actual = solve(args)
except Exception as exc:
actual = 'raised ' + type(exc).__name__
check(label, actual, 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: magnitude for shares | [['pool', 'D', 7], ['mkt', 'C', -4], ['hr', 'C', -1], ['it', 'C', -2]] | [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]] | Failed |
| control 1 | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | Passed |
| control 2 | [['pool', 'C', 7], ['fin', 'D', 7]] | [['pool', 'C', 7], ['fin', 'D', 7]] | Passed |
| control 3 | [['pool', 'C', 99999], ['hr', 'D', 99999]] | [['pool', 'C', 99999], ['hr', 'D', 99999]] | Passed |
| control 4 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
| control 5 | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | Passed |
| control 6 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
SHA-256 / e3c38941344503c3002c95d79877cc2ebf7a47245f5b395a055413c7d3ba76bc
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
amt = x['amount']
side_src, side_dst = ('C', 'D') if amt >= 0 else ('D', 'C')
mag = abs(amt)
ws = [(c, w) for c, w in x['weights'] if w > 0]
total = sum(w for _, w in ws)
base = [amt * w // total for _, w in ws]
rems = [mag * w % total for _, w in ws]
left = mag - sum(base)
order = sorted(range(len(ws)), key=lambda i: (-rems[i], i))
for i in order[:left]:
base[i] += 1
lines = [[x['source'], side_src, mag]]
for (c, w), share in zip(ws, base):
if share:
lines.append([c, side_dst, share])
return lines
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: magnitude for shares', {'amount': -7, 'weights': [['ops', 0], ['mkt', 5], ['hr', 1], ['it', 2], ['lab', 0]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]]], ['control 1', {'amount': 7, 'weights': [['fin', 0], ['it', 7], ['hr', 2], ['lab', 3], ['ops', 2]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]]], ['control 2', {'amount': 7, 'weights': [['mkt', 0], ['fin', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 7]]], ['control 3', {'amount': 99999, 'weights': [['hr', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 99999], ['hr', 'D', 99999]]], ['control 4', {'amount': 0, 'weights': [['ops', 3], ['mkt', 7], ['fin', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 5', {'amount': 100, 'weights': [['ops', 5], ['it', 5]], 'source': 'pool'}, [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]]], ['control 6', {'amount': 0, 'weights': [['ops', 5], ['hr', 5], ['mkt', 7], ['fin', 3]], 'source': 'pool'}, [['pool', 'C', 0]]]], [['regression: magnitude for shares', {'amount': -101, 'weights': [['lab', 1], ['mkt', 5], ['ops', 2]], 'source': 'pool'}, [['pool', 'D', 101], ['lab', 'C', 13], ['mkt', 'C', 63], ['ops', 'C', 25]]], ['control 1', {'amount': 7, 'weights': [['mkt', 0], ['it', 7], ['ops', 2], ['fin', 2], ['lab', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['ops', 'D', 1], ['fin', 'D', 1], ['lab', 'D', 1]]], ['control 2', {'amount': 0, 'weights': [['it', 3], ['lab', 1], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 3', {'amount': 101, 'weights': [['lab', 7], ['hr', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['lab', 'D', 59], ['hr', 'D', 42]]], ['control 4', {'amount': 10, 'weights': [['lab', 1], ['it', 3], ['hr', 1], ['ops', 7], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 2], ['hr', 'D', 1], ['ops', 'D', 6]]], ['control 5', {'amount': 10, 'weights': [['mkt', 1], ['it', 2], ['fin', 1], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 2], ['fin', 'D', 1], ['hr', 'D', 6]]], ['control 6', {'amount': 1000, 'weights': [['mkt', 2], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 1000], ['mkt', 'D', 286], ['fin', 'D', 714]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['mkt', 7], ['fin', 7]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['fin', 'C', 3]]], ['control 1', {'amount': 7, 'weights': [['fin', 1], ['mkt', 5]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 1], ['mkt', 'D', 6]]], ['control 2', {'amount': 7, 'weights': [['it', 0], ['lab', 7], ['mkt', 1], ['hr', 3]], 'source': 'pool'}, [['pool', 'C', 7], ['lab', 'D', 4], ['mkt', 'D', 1], ['hr', 'D', 2]]], ['control 3', {'amount': 3, 'weights': [['it', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 3]]], ['control 4', {'amount': 10, 'weights': [['ops', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['lab', 'D', 6]]], ['control 5', {'amount': 1000, 'weights': [['ops', 7], ['mkt', 5], ['fin', 7]], 'source': 'pool'}, [['pool', 'C', 1000], ['ops', 'D', 369], ['mkt', 'D', 263], ['fin', 'D', 368]]], ['control 6', {'amount': 10, 'weights': [['ops', 1], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 2], ['lab', 'D', 8]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['lab', 2], ['ops', 7], ['mkt', 2]], 'source': 'pool'}, [['pool', 'D', 7], ['lab', 'C', 1], ['ops', 'C', 5], ['mkt', 'C', 1]]], ['control 1', {'amount': 100, 'weights': [['it', 7], ['fin', 3], ['mkt', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 100], ['it', 'D', 39], ['fin', 'D', 17], ['mkt', 'D', 39], ['hr', 'D', 5]]], ['control 2', {'amount': 10, 'weights': [['lab', 2], ['it', 5], ['hr', 7], ['mkt', 0], ['ops', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 3], ['hr', 'D', 3], ['ops', 'D', 3]]], ['control 3', {'amount': 1000, 'weights': [['fin', 7], ['mkt', 3], ['it', 3], ['lab', 1], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 1000], ['fin', 'D', 438], ['mkt', 'D', 188], ['it', 'D', 187], ['lab', 'D', 62], ['hr', 'D', 125]]], ['control 4', {'amount': 3, 'weights': [['it', 3], ['lab', 3], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 1], ['lab', 'D', 1], ['hr', 'D', 1]]], ['control 5', {'amount': 99999, 'weights': [['hr', 0], ['lab', 0], ['ops', 3], ['mkt', 5], ['it', 2]], 'source': 'pool'}, [['pool', 'C', 99999], ['ops', 'D', 30000], ['mkt', 'D', 49999], ['it', 'D', 20000]]], ['control 6', {'amount': 101, 'weights': [['mkt', 3], ['hr', 0], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['mkt', 'D', 38], ['fin', 'D', 63]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['fin', 3], ['mkt', 1]], 'source': 'pool'}, [['pool', 'D', 7], ['fin', 'C', 5], ['mkt', 'C', 2]]], ['control 1', {'amount': 100, 'weights': [['fin', 2], ['hr', 0], ['it', 0], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 100], ['fin', 'D', 100]]], ['control 2', {'amount': 10, 'weights': [['ops', 3], ['it', 1], ['mkt', 3], ['hr', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['it', 'D', 2], ['mkt', 'D', 4]]], ['control 3', {'amount': 7, 'weights': [['mkt', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 7], ['mkt', 'D', 7]]], ['control 4', {'amount': 10, 'weights': [['mkt', 1], ['it', 7], ['fin', 0], ['ops', 1]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 8], ['ops', 'D', 1]]], ['control 5', {'amount': 101, 'weights': [['fin', 5], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 72], ['hr', 'D', 29]]], ['control 6', {'amount': 101, 'weights': [['fin', 2], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 51], ['hr', 'D', 50]]]]]
for label, args, expected in fixtures[N-1]:
try:
actual = solve(args)
except Exception as exc:
actual = 'raised ' + type(exc).__name__
check(label, actual, 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: magnitude for shares | [['pool', 'D', 7], ['mkt', 'C', -4], ['it', 'C', -1]] | [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]] | Failed |
| control 1 | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | Passed |
| control 2 | [['pool', 'C', 7], ['fin', 'D', 7]] | [['pool', 'C', 7], ['fin', 'D', 7]] | Passed |
| control 3 | [['pool', 'C', 99999], ['hr', 'D', 99999]] | [['pool', 'C', 99999], ['hr', 'D', 99999]] | Passed |
| control 4 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
| control 5 | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | Passed |
| control 6 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
SHA-256 / ce49a4e80c8ea7ddb5c36d5b80b8e209735d45f9567a21966fdbf776db77834c
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
amt = x['amount']
side_src, side_dst = ('C', 'D') if amt >= 0 else ('D', 'C')
mag = abs(amt)
ws = [(c, w) for c, w in x['weights'] if w > 0]
total = sum(w for _, w in ws)
base = [mag * w // total for _, w in ws]
rems = [mag * w % total for _, w in ws]
left = mag - sum(base)
order = sorted(range(len(ws)), key=lambda i: (-rems[i], i))
for i in order[:left]:
base[i] += 1
lines = [[x['source'], side_src, mag]]
for (c, w), share in zip(ws, base):
if share:
lines.append([c, side_dst, share])
return lines
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: magnitude for shares', {'amount': -7, 'weights': [['ops', 0], ['mkt', 5], ['hr', 1], ['it', 2], ['lab', 0]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]]], ['control 1', {'amount': 7, 'weights': [['fin', 0], ['it', 7], ['hr', 2], ['lab', 3], ['ops', 2]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]]], ['control 2', {'amount': 7, 'weights': [['mkt', 0], ['fin', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 7]]], ['control 3', {'amount': 99999, 'weights': [['hr', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 99999], ['hr', 'D', 99999]]], ['control 4', {'amount': 0, 'weights': [['ops', 3], ['mkt', 7], ['fin', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 5', {'amount': 100, 'weights': [['ops', 5], ['it', 5]], 'source': 'pool'}, [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]]], ['control 6', {'amount': 0, 'weights': [['ops', 5], ['hr', 5], ['mkt', 7], ['fin', 3]], 'source': 'pool'}, [['pool', 'C', 0]]]], [['regression: magnitude for shares', {'amount': -101, 'weights': [['lab', 1], ['mkt', 5], ['ops', 2]], 'source': 'pool'}, [['pool', 'D', 101], ['lab', 'C', 13], ['mkt', 'C', 63], ['ops', 'C', 25]]], ['control 1', {'amount': 7, 'weights': [['mkt', 0], ['it', 7], ['ops', 2], ['fin', 2], ['lab', 1]], 'source': 'pool'}, [['pool', 'C', 7], ['it', 'D', 4], ['ops', 'D', 1], ['fin', 'D', 1], ['lab', 'D', 1]]], ['control 2', {'amount': 0, 'weights': [['it', 3], ['lab', 1], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 0]]], ['control 3', {'amount': 101, 'weights': [['lab', 7], ['hr', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['lab', 'D', 59], ['hr', 'D', 42]]], ['control 4', {'amount': 10, 'weights': [['lab', 1], ['it', 3], ['hr', 1], ['ops', 7], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 2], ['hr', 'D', 1], ['ops', 'D', 6]]], ['control 5', {'amount': 10, 'weights': [['mkt', 1], ['it', 2], ['fin', 1], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 2], ['fin', 'D', 1], ['hr', 'D', 6]]], ['control 6', {'amount': 1000, 'weights': [['mkt', 2], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 1000], ['mkt', 'D', 286], ['fin', 'D', 714]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['mkt', 7], ['fin', 7]], 'source': 'pool'}, [['pool', 'D', 7], ['mkt', 'C', 4], ['fin', 'C', 3]]], ['control 1', {'amount': 7, 'weights': [['fin', 1], ['mkt', 5]], 'source': 'pool'}, [['pool', 'C', 7], ['fin', 'D', 1], ['mkt', 'D', 6]]], ['control 2', {'amount': 7, 'weights': [['it', 0], ['lab', 7], ['mkt', 1], ['hr', 3]], 'source': 'pool'}, [['pool', 'C', 7], ['lab', 'D', 4], ['mkt', 'D', 1], ['hr', 'D', 2]]], ['control 3', {'amount': 3, 'weights': [['it', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 3]]], ['control 4', {'amount': 10, 'weights': [['ops', 3], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['lab', 'D', 6]]], ['control 5', {'amount': 1000, 'weights': [['ops', 7], ['mkt', 5], ['fin', 7]], 'source': 'pool'}, [['pool', 'C', 1000], ['ops', 'D', 369], ['mkt', 'D', 263], ['fin', 'D', 368]]], ['control 6', {'amount': 10, 'weights': [['ops', 1], ['lab', 5]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 2], ['lab', 'D', 8]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['lab', 2], ['ops', 7], ['mkt', 2]], 'source': 'pool'}, [['pool', 'D', 7], ['lab', 'C', 1], ['ops', 'C', 5], ['mkt', 'C', 1]]], ['control 1', {'amount': 100, 'weights': [['it', 7], ['fin', 3], ['mkt', 7], ['hr', 1]], 'source': 'pool'}, [['pool', 'C', 100], ['it', 'D', 39], ['fin', 'D', 17], ['mkt', 'D', 39], ['hr', 'D', 5]]], ['control 2', {'amount': 10, 'weights': [['lab', 2], ['it', 5], ['hr', 7], ['mkt', 0], ['ops', 7]], 'source': 'pool'}, [['pool', 'C', 10], ['lab', 'D', 1], ['it', 'D', 3], ['hr', 'D', 3], ['ops', 'D', 3]]], ['control 3', {'amount': 1000, 'weights': [['fin', 7], ['mkt', 3], ['it', 3], ['lab', 1], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 1000], ['fin', 'D', 438], ['mkt', 'D', 188], ['it', 'D', 187], ['lab', 'D', 62], ['hr', 'D', 125]]], ['control 4', {'amount': 3, 'weights': [['it', 3], ['lab', 3], ['hr', 7]], 'source': 'pool'}, [['pool', 'C', 3], ['it', 'D', 1], ['lab', 'D', 1], ['hr', 'D', 1]]], ['control 5', {'amount': 99999, 'weights': [['hr', 0], ['lab', 0], ['ops', 3], ['mkt', 5], ['it', 2]], 'source': 'pool'}, [['pool', 'C', 99999], ['ops', 'D', 30000], ['mkt', 'D', 49999], ['it', 'D', 20000]]], ['control 6', {'amount': 101, 'weights': [['mkt', 3], ['hr', 0], ['fin', 5]], 'source': 'pool'}, [['pool', 'C', 101], ['mkt', 'D', 38], ['fin', 'D', 63]]]], [['regression: magnitude for shares', {'amount': -7, 'weights': [['fin', 3], ['mkt', 1]], 'source': 'pool'}, [['pool', 'D', 7], ['fin', 'C', 5], ['mkt', 'C', 2]]], ['control 1', {'amount': 100, 'weights': [['fin', 2], ['hr', 0], ['it', 0], ['mkt', 0]], 'source': 'pool'}, [['pool', 'C', 100], ['fin', 'D', 100]]], ['control 2', {'amount': 10, 'weights': [['ops', 3], ['it', 1], ['mkt', 3], ['hr', 0]], 'source': 'pool'}, [['pool', 'C', 10], ['ops', 'D', 4], ['it', 'D', 2], ['mkt', 'D', 4]]], ['control 3', {'amount': 7, 'weights': [['mkt', 1], ['it', 0]], 'source': 'pool'}, [['pool', 'C', 7], ['mkt', 'D', 7]]], ['control 4', {'amount': 10, 'weights': [['mkt', 1], ['it', 7], ['fin', 0], ['ops', 1]], 'source': 'pool'}, [['pool', 'C', 10], ['mkt', 'D', 1], ['it', 'D', 8], ['ops', 'D', 1]]], ['control 5', {'amount': 101, 'weights': [['fin', 5], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 72], ['hr', 'D', 29]]], ['control 6', {'amount': 101, 'weights': [['fin', 2], ['hr', 2]], 'source': 'pool'}, [['pool', 'C', 101], ['fin', 'D', 51], ['hr', 'D', 50]]]]]
for label, args, expected in fixtures[N-1]:
try:
actual = solve(args)
except Exception as exc:
actual = 'raised ' + type(exc).__name__
check(label, actual, 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: magnitude for shares | [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]] | [['pool', 'D', 7], ['mkt', 'C', 4], ['hr', 'C', 1], ['it', 'C', 2]] | Passed |
| control 1 | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | [['pool', 'C', 7], ['it', 'D', 4], ['hr', 'D', 1], ['lab', 'D', 1], ['ops', 'D', 1]] | Passed |
| control 2 | [['pool', 'C', 7], ['fin', 'D', 7]] | [['pool', 'C', 7], ['fin', 'D', 7]] | Passed |
| control 3 | [['pool', 'C', 99999], ['hr', 'D', 99999]] | [['pool', 'C', 99999], ['hr', 'D', 99999]] | Passed |
| control 4 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
| control 5 | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | [['pool', 'C', 100], ['ops', 'D', 50], ['it', 'D', 50]] | Passed |
| control 6 | [['pool', 'C', 0]] | [['pool', 'C', 0]] | Passed |
SHA-256 / 0120c394718225d13079d534593dc30c3a2b3e7d865b8b8f5db4b34ca2b3c7e5
Verification & scope
A deterministic bounded teaching model with stipulated toy bookkeeping rules stated in the contract; amounts are integer cents; it makes no claim of conformance to any accounting standard or product. 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 2026-09-29T14:46:24.108516+00:00.
Case digest / 7ca5fadc79432edfdfca7121898e3bdb5f7d7246bb331695d26b486b20541650