FA-12496 / Biological sequence representation / Open access

Ambiguous sequence symbols are compared as literal letters · case 01

Ambiguous sequence symbols are compared as literal letters.

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

ROOT CAUSE

Literal equality ignores possible-base sets.

THE FAILURE

Literal equality ignores possible-base sets.

Unsuccessful approach: Subset comparison requires certainty although the contract asks possibility.

Case contract

For equal-length strings over A,C,G,T,R,N, return whether every aligned pair has intersecting sets; R={A,G}, N={A,C,G,T}. Unequal lengths are false.

Why this case matters

An offline abstract sequence-data model; useful for testing representation invariants without biological inference.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(a,b):
    return a==b
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('variable ambiguity', solve('R'*N,'A'*N), True)
check('incompatible', solve('R','C'), False)
check('unknown possible', solve('N','T'), True)
check('empty', solve('',''), True)
check('length', solve('A','AA'), False)
check('late mismatch', solve('NA','TC'), False)
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
variable ambiguity	`False`	`True`	Failed
incompatible	`False`	`False`	Passed
unknown possible	`False`	`True`	Failed
empty	`True`	`True`	Passed
length	`False`	`False`	Passed
late mismatch	`False`	`False`	Passed

SHA-256 / 3bf2cd4692ec36681cf8126d5913d42441359af72d056b987175bb551a397077

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(a,b):
    m={'A':set('A'),'C':set('C'),'G':set('G'),'T':set('T'),'R':set('AG'),'N':set('ACGT')}
    return len(a)==len(b) and all(m[x]<=m[y] for x,y in zip(a,b))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('variable ambiguity', solve('R'*N,'A'*N), True)
check('incompatible', solve('R','C'), False)
check('unknown possible', solve('N','T'), True)
check('empty', solve('',''), True)
check('length', solve('A','AA'), False)
check('late mismatch', solve('NA','TC'), False)
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
variable ambiguity	`False`	`True`	Failed
incompatible	`False`	`False`	Passed
unknown possible	`False`	`True`	Failed
empty	`True`	`True`	Passed
length	`False`	`False`	Passed
late mismatch	`False`	`False`	Passed

SHA-256 / 40c7e4aeef86697e33f73f4508ec95597ee15e195c9f17317e5a2246ef8606d0

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.

Member access is invitation-based. Sign in with your invited account to inspect the repair.

Verification & scope

Synthetic strings and explicit policies only; no biological interpretation or laboratory workflow. 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 2026-09-29T14:38:57.484891+00:00.

Case digest / a4a41eb948d9588d748a7d8c551f355b5b1e5c0b4f0445b0815bc267ac2d546f