FA-4891 / Call argument binding / Open access

Variadic positional binding: Flattens nested positional values while collecting tail · case 01

Flattens nested positional values while collecting tail and changes the required Python-language result.

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

ROOT CAUSE

Flattens nested positional values while collecting tail. The executable reproducer isolates this operation from the rest of the contract.

VERIFIED REPAIR

Call f(a, *tail, flag=False), returning [a,list(tail),flag]. flag must be named; arbitrary extra positions belong to tail.

Unsuccessful approach: The alternative still fails because it drops the first variadic argument after binding.

Case contract

Call f(a, *tail, flag=False), returning [a,list(tail),flag]. flag must be named; arbitrary extra positions belong to tail. Inputs use the finite Python types shown in the fixtures. An error string denotes the specified caught exception, not an unhandled process failure.

Why this case matters

Runs Python standard-library language operations in a deterministic local reproducer. Literal expected answers are authored independently. Related defects share an evaluation group to avoid benchmark split leakage.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(args, kwargs):
    def f(a, *tail, flag=False):
        return [a,[item for v in tail for item in (v if isinstance(v,list) else [v])],flag]
    try:
        return f(*args, **kwargs)
    except TypeError:
        return "TypeError"
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('only required', solve([1], {}), [1, [], False])
check('several extras', solve([1, 2, 3], {}), [1, [2, 3], False])
check('named flag', solve([1, 2], {'flag': True}), [1, [2], True])
check('nested tail preserved', solve([1, [2, 3]], {}), [1, [[2, 3]], False])
check('unknown keyword', solve([1], {'other': 2}), 'TypeError')
check('missing required', solve([], {}), 'TypeError')
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
only required	`[1, [], False]`	`[1, [], False]`	Passed
several extras	`[1, [2, 3], False]`	`[1, [2, 3], False]`	Passed
named flag	`[1, [2], True]`	`[1, [2], True]`	Passed
nested tail preserved	`[1, [2, 3], False]`	`[1, [[2, 3]], False]`	Failed
unknown keyword	`TypeError`	`TypeError`	Passed
missing required	`TypeError`	`TypeError`	Passed

SHA-256 / f590178f50b60774948cfa44d33d50f30111b23a9f5d75f34bad9afa2c7b1d22

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(args, kwargs):
    def f(a, *tail, flag=False):
        return [a,list(tail[1:]),flag]
    try:
        return f(*args, **kwargs)
    except TypeError:
        return "TypeError"
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('only required', solve([1], {}), [1, [], False])
check('several extras', solve([1, 2, 3], {}), [1, [2, 3], False])
check('named flag', solve([1, 2], {'flag': True}), [1, [2], True])
check('nested tail preserved', solve([1, [2, 3]], {}), [1, [[2, 3]], False])
check('unknown keyword', solve([1], {'other': 2}), 'TypeError')
check('missing required', solve([], {}), 'TypeError')
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
only required	`[1, [], False]`	`[1, [], False]`	Passed
several extras	`[1, [3], False]`	`[1, [2, 3], False]`	Failed
named flag	`[1, [], True]`	`[1, [2], True]`	Failed
nested tail preserved	`[1, [], False]`	`[1, [[2, 3]], False]`	Failed
unknown keyword	`TypeError`	`TypeError`	Passed
missing required	`TypeError`	`TypeError`	Passed

SHA-256 / b041e88f271e3abecd95ef47062035f7c8e9bef889719f080a710165b2983432

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(args, kwargs):
    def f(a, *tail, flag=False):
        return [a,list(tail),flag]
    try:
        return f(*args, **kwargs)
    except TypeError:
        return "TypeError"
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('only required', solve([1], {}), [1, [], False])
check('several extras', solve([1, 2, 3], {}), [1, [2, 3], False])
check('named flag', solve([1, 2], {'flag': True}), [1, [2], True])
check('nested tail preserved', solve([1, [2, 3]], {}), [1, [[2, 3]], False])
check('unknown keyword', solve([1], {'other': 2}), 'TypeError')
check('missing required', solve([], {}), 'TypeError')
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
only required	`[1, [], False]`	`[1, [], False]`	Passed
several extras	`[1, [2, 3], False]`	`[1, [2, 3], False]`	Passed
named flag	`[1, [2], True]`	`[1, [2], True]`	Passed
nested tail preserved	`[1, [[2, 3]], False]`	`[1, [[2, 3]], False]`	Passed
unknown keyword	`TypeError`	`TypeError`	Passed
missing required	`TypeError`	`TypeError`	Passed

SHA-256 / 4ac73ad54c79a5d43136214b918328ca30ee71b3109960da0e81e9c5678cfc8e

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 2026-09-29T14:37:43.833932+00:00.

Case digest / 05b470d62804d4eff04e36377d9d6c90749bc9b49fc4003ec741223ec491234f