FA-11381 / Spreadsheet calculation semantics / Open access

Percent formatting changes the stored numeric value · case 01

Applying percentage formatting multiplies the stored cell value.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The rendering scale is written back into numeric storage.

THE FAILURE

The rendering scale is written back into numeric storage.

Unsuccessful approach: Dividing stored inputs by a hundred assumes they were whole percentage points rather than fractions.

Case contract

For a finite float input whose binary floating-point product value*100 is also finite, and decimal places 0..3, return [unchanged stored value, fixed-point display of that product with percent suffix]. This is a formatting-only operation using Python float formatting, not exact decimal arithmetic.

Why this case matters

This isolated spreadsheet model makes cell semantics explicit; it does not claim compatibility with every workbook engine.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(value, places):
    return [value*100, format(value*100, f'.{places}f')+'%']
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fraction stored unchanged', solve(N/8,1), [N/8, f'{12.5*N:.1f}%'])
check('whole unit is hundred percent', solve(1,0), [1,'100%'])
check('zero percent', solve(0,2), [0,'0.00%'])
check('negative fraction', solve(-0.5,0), [-0.5,'-50%'])
check('above hundred percent', solve(2,1), [2,'200.0%'])
check('three decimal places', solve(0.125,3), [0.125,'12.500%'])
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
fraction stored unchanged	`[12.5, '12.5%']`	`[0.125, '12.5%']`	Failed
whole unit is hundred percent	`[100, '100%']`	`[1, '100%']`	Failed
zero percent	`[0, '0.00%']`	`[0, '0.00%']`	Passed
negative fraction	`[-50.0, '-50%']`	`[-0.5, '-50%']`	Failed
above hundred percent	`[200, '200.0%']`	`[2, '200.0%']`	Failed
three decimal places	`[12.5, '12.500%']`	`[0.125, '12.500%']`	Failed

SHA-256 / ff833bc980df5ad5007b46b37b3686574293bed224ee04f5b5c7d075eef041d2

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(value, places):
    return [value/100, format(value, f'.{places}f')+'%']
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fraction stored unchanged', solve(N/8,1), [N/8, f'{12.5*N:.1f}%'])
check('whole unit is hundred percent', solve(1,0), [1,'100%'])
check('zero percent', solve(0,2), [0,'0.00%'])
check('negative fraction', solve(-0.5,0), [-0.5,'-50%'])
check('above hundred percent', solve(2,1), [2,'200.0%'])
check('three decimal places', solve(0.125,3), [0.125,'12.500%'])
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
fraction stored unchanged	`[0.00125, '0.1%']`	`[0.125, '12.5%']`	Failed
whole unit is hundred percent	`[0.01, '1%']`	`[1, '100%']`	Failed
zero percent	`[0.0, '0.00%']`	`[0, '0.00%']`	Passed
negative fraction	`[-0.005, '-0%']`	`[-0.5, '-50%']`	Failed
above hundred percent	`[0.02, '2.0%']`	`[2, '200.0%']`	Failed
three decimal places	`[0.00125, '0.125%']`	`[0.125, '12.500%']`	Failed

SHA-256 / caa7d243360ad118a806a54b6f7f5c011536bb52bd4fba3eaa9ed138839ae7b3

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 6 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

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 2026-09-29T14:38:47.444112+00:00.

Case digest / bd16361e8807699e6dfd68c8a3ca8f160c0d80fc529c0e7dc99f4ff05e8adeb9