混合检索的 RRF：把两份排名合成可解释的结果

"""One offline RRF input-order experiment; no search engine or model is run.

rrf_demo.py is the unchanged code copied from the existing published article.
All scores and rankings here are authored fixtures, not measured similarities.
"""
from dataclasses import dataclass
from decimal import Decimal
from itertools import permutations
import json
import platform

from rrf_demo import fuse


@dataclass(frozen=True)
class Hit:
    doc_id: str
    score: Decimal


@dataclass(frozen=True)
class Batch:
    partition: str
    score_contract: str
    hits: tuple[Hit, ...]


# This label declares a toy assumption. Matching labels cannot certify real
# score comparability, embedding identity, query identity, or index versions.
CONTRACT = "authored-score-v1/same-query/same-snapshot/higher-is-better"
A = Batch("partition_a", CONTRACT, (
    Hit("a", Decimal("0.81")),
    Hit("b", Decimal("0.79")),
    Hit("c", Decimal("0.77")),
))
B = Batch("partition_b", CONTRACT, (Hit("target", Decimal("0.96")),))
DOCS = {d: {"doc_id": d, "source": "fixture/" + d + ".txt"}
        for d in ("a", "b", "c", "target")}
SECOND_ROUTE = ("target", "a", "b", "c")


def arrival_ids(batches):
    """Intentionally flawed baseline: transport position becomes search rank."""
    return [hit.doc_id for batch in batches for hit in batch.hits]


def merge_comparable(batches, expected_contract=CONTRACT):
    """Order only the supplied candidates under one explicit comparable scale.

    No claim of complete corpus recall. Duplicate IDs are rejected rather than
    silently deciding between overlapping partitions or inconsistent scores.
    This is an independent toy merge convention, not a product implementation.
    """
    rows = []
    seen_partitions, seen_ids = set(), set()
    for batch in batches:
        if batch.score_contract != expected_contract:
            raise ValueError("score_contract_mismatch")
        if not batch.partition or batch.partition in seen_partitions:
            raise ValueError("duplicate_or_empty_partition")
        seen_partitions.add(batch.partition)
        for hit in batch.hits:
            if not hit.doc_id or hit.doc_id in seen_ids:
                raise ValueError("duplicate_or_empty_document")
            if type(hit.score) is not Decimal or not hit.score.is_finite():
                raise ValueError("finite_decimal_score_required")
            seen_ids.add(hit.doc_id)
            rows.append(hit)
    # New list: do not mutate a caller's batch, row, score, or existing order.
    return [hit.doc_id for hit in sorted(rows, key=lambda h: (h.score.copy_negate(), h.doc_id))]


def fused(first_route, *, window=4, size=4):
    """Run the EXISTING article's equal-weight RRF without changing its formula."""
    result = fuse({"partitioned_fixture": first_route,
                   "second_fixture": list(SECOND_ROUTE)},
                  DOCS, {}, k=60, window=window, size=size)
    return {"candidates": result["candidates"], "hits": [
        {"doc_id": row["doc_id"], "exact_score": row["exact_score"],
         "ranks": {route: trace["rank"] for route, trace in row["ranks"].items()}}
        for row in result["hits"]]}


def report():
    cases = []
    for batches in ((A, B), (B, A)):
        raw, ordered = arrival_ids(batches), merge_comparable(batches)
        cases.append({
            "arrival": [b.partition for b in batches],
            "naive_route": raw,
            "naive_fusion": fused(raw),
            "merged_route": ordered,
            "merged_fusion": fused(ordered),
            "naive_top1": fused(raw, size=1)["hits"][0]["doc_id"],
            "merged_top1": fused(ordered, size=1)["hits"][0]["doc_id"],
        })
    permutations_checked = 0
    permutation_results = []
    for a_hits in permutations(A.hits):
        a = Batch(A.partition, CONTRACT, a_hits)
        for batches in ((a, B), (B, a)):
            if merge_comparable(batches) != list(SECOND_ROUTE):
                raise AssertionError("merged route changed across permutations")
            if fused(merge_comparable(batches)) != fused(list(SECOND_ROUTE)):
                raise AssertionError("fusion changed across permutations")
            permutations_checked += 1
            permutation_results.append({
                "arrival": [b.partition for b in batches],
                "a_internal_order": [h.doc_id for h in a_hits],
                "naive_route": arrival_ids(batches),
                "naive_fusion": fused(arrival_ids(batches)),
                "merged_route": merge_comparable(batches),
                "merged_fusion": fused(merge_comparable(batches)),
            })
    # Information already discarded cannot be recreated by subsequent sorting.
    early_cut = (Batch("already_truncated", CONTRACT, A.hits),)
    recovered = merge_comparable(early_cut)
    full = merge_comparable((A, B))
    return {
        "python": platform.python_version(),
        "input_kind": "original authored scores and ranked lists; no retrieval/model run",
        "policy": "one logical route; globally order its supplied comparable candidates",
        "input_batches": [{"partition": b.partition, "score_contract": b.score_contract,
                           "hits": [{"doc_id": h.doc_id, "score": str(h.score)} for h in b.hits]}
                          for b in (A, B)],
        "second_route": list(SECOND_ROUTE),
        "parameters": {"k": 60, "window": 4, "size": 4, "top1_size": 1},
        "cases": cases,
        "permutation_results": permutation_results,
        "permutations_checked": permutations_checked,
        "single_sorted_batch": {"arrival": arrival_ids((A,)),
                                "merged": merge_comparable((A,))},
        "cut_before_merge": {"kept_ids": recovered,
                             "target_in_first_route": "target" in recovered,
                             "target_still_in_second_route": "target" in SECOND_ROUTE,
                             "fusion_after_lost_first_route_contribution": fused(recovered),
                             "warning": "second route may still retrieve target; missing first-route evidence is not restored"},
        "merge_then_route_window_1": fused(full, window=1, size=1),
        "naive_then_route_window_1": fused(arrival_ids((A, B)), window=1, size=1),
        "limits": [
            "Same-contract label is only a declared fixture assumption, not proof of comparable real scores",
            "Never sort unrelated BM25 and vector scores together",
            "Separate-list RRF is another valid design with different semantics; not implemented here",
            "No async scheduler, WeKnora deployment, Elasticsearch instance, embeddings, ANN or reranker tested",
            "Only supplied candidates are ordered; missing candidates are not recovered",
        ],
    }


if __name__ == "__main__":
    print(json.dumps(report(), ensure_ascii=False, indent=2))

"""Deterministic positive/negative controls for one RRF input-order boundary."""
from dataclasses import replace
from decimal import Decimal, localcontext
from fractions import Fraction
from itertools import permutations
import unittest

from fixed_oracle import BAD, GOOD

from probe import (A, B, CONTRACT, SECOND_ROUTE, Batch, Hit, arrival_ids,
                   fused, merge_comparable, report)


class ArrivalOrderTests(unittest.TestCase):
    def test_local_sorted_batches_are_not_global_sorted(self):
        self.assertEqual(arrival_ids((A, B)), ["a", "b", "c", "target"])
        self.assertEqual(merge_comparable((A, B)), ["target", "a", "b", "c"])

    def test_only_arrival_order_changes_naive_top1(self):
        self.assertEqual(fused(arrival_ids((A, B))), BAD)
        self.assertEqual(fused(arrival_ids((A, B)), size=1)["hits"][0]["doc_id"], "a")
        self.assertEqual(fused(arrival_ids((B, A))), GOOD)
        self.assertEqual(fused(arrival_ids((B, A)), size=1)["hits"][0]["doc_id"], "target")

    def test_all_12_fixture_permutations_preserve_correct_fusion(self):
        expected = GOOD
        count = 0
        for a_hits in permutations(A.hits):
            for batches in ((replace(A, hits=a_hits), B), (B, replace(A, hits=a_hits))):
                self.assertEqual(fused(merge_comparable(batches)), expected)
                count += 1
        self.assertEqual(count, 12)

    def test_exact_contributions_explain_flip(self):
        bad = {r["doc_id"]: r for r in fused(arrival_ids((A, B)))["hits"]}
        good = {r["doc_id"]: r for r in fused(merge_comparable((A, B)))["hits"]}
        self.assertEqual(Fraction(bad["a"]["exact_score"]), Fraction(1,61)+Fraction(1,62))
        self.assertEqual(Fraction(bad["target"]["exact_score"]), Fraction(1,64)+Fraction(1,61))
        self.assertEqual(good["target"]["exact_score"], "2/61")
        self.assertEqual(good["target"]["ranks"]["partitioned_fixture"], 1)

    def test_single_sorted_batch_is_noop(self):
        self.assertEqual(merge_comparable((A,)), arrival_ids((A,)))
        self.assertEqual(merge_comparable((B,)), arrival_ids((B,)))

    def test_exact_decimal_order_and_stable_ties(self):
        x = Batch("x", CONTRACT, (Hit("z", Decimal("0.9")),))
        y = Batch("y", CONTRACT, (Hit("a", Decimal("0.9")),))
        self.assertEqual(merge_comparable((x,y)), ["a","z"])
        self.assertEqual(merge_comparable((y,x)), ["a","z"])
        # Unary minus would round these keys at the default Decimal precision.
        lower = Batch("lower", CONTRACT, (Hit("a", Decimal("0.90000000000000000000000000001")),))
        higher = Batch("higher", CONTRACT, (Hit("z", Decimal("0.90000000000000000000000000002")),))
        with localcontext() as context:
            context.prec = 2
            self.assertEqual(merge_comparable((lower,higher)), ["z","a"])
            self.assertEqual(merge_comparable((higher,lower)), ["z","a"])

    def test_other_score_contract_is_rejected(self):
        for label in ("bm25/lower-is-better", "different-query", "different-model", "different-snapshot"):
            with self.subTest(label=label), self.assertRaisesRegex(ValueError, "score_contract_mismatch"):
                merge_comparable((A, replace(B, score_contract=label)))

    def test_nonfinite_or_nondecimal_scores_are_rejected(self):
        for score in (Decimal("NaN"), Decimal("Infinity"), Decimal("-Infinity"), 0.9, True):
            with self.subTest(score=score), self.assertRaisesRegex(ValueError, "finite_decimal"):
                merge_comparable((replace(B, hits=(Hit("target", score),)),))

    def test_duplicate_partition_or_document_is_rejected(self):
        with self.assertRaisesRegex(ValueError, "duplicate_or_empty_partition"):
            merge_comparable((A,A))
        with self.assertRaisesRegex(ValueError, "duplicate_or_empty_document"):
            merge_comparable((A,replace(B, hits=(Hit("a",Decimal("0.99")),))))

    def test_empty_batch_and_no_mutation(self):
        before = repr((A,B))
        empty = Batch("empty", CONTRACT, ())
        self.assertEqual(merge_comparable((empty,)), [])
        self.assertEqual(merge_comparable((A,empty,B)), list(SECOND_ROUTE))
        self.assertEqual(repr((A,B)), before)

    def test_early_cut_cannot_restore_missing_route_evidence(self):
        cut = (Batch("cut", CONTRACT, A.hits),)
        merged = merge_comparable(cut)
        self.assertNotIn("target", merged)
        hit = next(r for r in fused(merged)["hits"] if r["doc_id"] == "target")
        self.assertEqual(hit["exact_score"], "1/61")
        self.assertEqual(hit["ranks"], {"second_fixture":1})

    def test_route_window_and_display_size_remain_distinct(self):
        bad = fused(arrival_ids((A,B)),window=1,size=1)
        good = fused(merge_comparable((A,B)),window=1,size=1)
        self.assertEqual(bad["hits"][0]["doc_id"], "a")
        self.assertEqual(bad["hits"][0]["exact_score"], "1/61")
        self.assertEqual(good["hits"][0]["doc_id"], "target")
        self.assertEqual(good["hits"][0]["exact_score"], "2/61")

    def test_report_is_deterministic(self):
        self.assertEqual(report(), report())
        self.assertEqual(report()["permutations_checked"], 12)


if __name__ == "__main__":
    unittest.main(verbosity=2)

"""Literal independently written expectations, not computed by the target code."""
# Each row is (doc_id, exact RRF score, first-route rank, second-route rank).
BAD_ROWS = (
    ("a", "123/3782", 1, 2),
    ("target", "125/3904", 4, 1),
    ("b", "125/3906", 2, 3),
    ("c", "127/4032", 3, 4),
)
GOOD_ROWS = (
    ("target", "2/61", 1, 1),
    ("a", "1/31", 2, 2),
    ("b", "2/63", 3, 3),
    ("c", "1/32", 4, 4),
)
EXPECTED_ROUTE = ["target", "a", "b", "c"]


def expected(rows, first_route):
    """Formatting only: every rank and exact score above is a literal."""
    return {"candidates": {
        "partitioned_fixture": list(first_route),
        "second_fixture": ["target", "a", "b", "c"],
    }, "hits": [{"doc_id": d, "exact_score": s, "ranks": {
        "partitioned_fixture": r1, "second_fixture": r2,
    }} for d, s, r1, r2 in rows]}


BAD = expected(BAD_ROWS, ["a", "b", "c", "target"])
GOOD = expected(GOOD_ROWS, EXPECTED_ROUTE)


def require_equal(actual, expected_value):
    if actual != expected_value:
        raise AssertionError(f"oracle mismatch: {actual!r} != {expected_value!r}")


def verify():
    # Import only after the fixed expectations have been defined.
    from dataclasses import replace
    from itertools import permutations
    from probe import A, B, arrival_ids, fused, merge_comparable
    require_equal(fused(arrival_ids((A, B))), BAD)
    require_equal(fused(arrival_ids((B, A))), GOOD)
    count = 0
    for order in permutations(A.hits):
        a = replace(A, hits=order)
        for batches in ((a, B), (B, a)):
            ordered = merge_comparable(batches)
            require_equal(ordered, EXPECTED_ROUTE)
            require_equal(fused(ordered), GOOD)
            count += 1
    require_equal(count, 12)
    return {"literal_oracle_passed": True, "permutations_checked": count,
            "bad": BAD, "good": GOOD}


if __name__ == "__main__":
    import json
    print(json.dumps(verify(), ensure_ascii=False, indent=2))

"""Run seven real source mutations in isolated directories; no external packages."""
import hashlib
import json
from pathlib import Path
import re
import subprocess
import sys
import tempfile

ROOT = Path(__file__).resolve().parent
MUTANTS = (
    ("arrival_as_rank", "sorted(rows, key=lambda h: (h.score.copy_negate(), h.doc_id))", "rows",
     "test_all_12_fixture_permutations_preserve_correct_fusion"),
    ("wrong_score_direction", "(h.score.copy_negate(), h.doc_id)", "(h.score, h.doc_id)",
     "test_local_sorted_batches_are_not_global_sorted"),
    ("unstable_equal_scores", "(h.score.copy_negate(), h.doc_id)", "(h.score.copy_negate(),)",
     "test_exact_decimal_order_and_stable_ties"),
    ("skip_score_contract", "if batch.score_contract != expected_contract:", "if False:",
     "test_other_score_contract_is_rejected"),
    ("cut_before_ordering", "sorted(rows, key=lambda h: (h.score.copy_negate(), h.doc_id))",
     "sorted(rows[:3], key=lambda h: (h.score.copy_negate(), h.doc_id))",
     "test_all_12_fixture_permutations_preserve_correct_fusion"),
    ("rounded_decimal_key", "(h.score.copy_negate(), h.doc_id)", "(-h.score, h.doc_id)",
     "test_exact_decimal_order_and_stable_ties"),
    ("changed_rrf_constant", "DOCS, {}, k=60, window=window, size=size)",
     "DOCS, {}, k=61, window=window, size=size)",
     "test_exact_contributions_explain_flip"),
)


def run():
    original = (ROOT / "probe.py").read_text()
    results = []
    for name, old, new, required_failure in MUTANTS:
        if original.count(old) != 1:
            raise RuntimeError("mutation target must occur exactly once: " + name)
        changed = original.replace(old, new, 1)
        with tempfile.TemporaryDirectory(prefix="rrf-mutant-") as tmp:
            directory = Path(tmp)
            for filename in ("rrf_demo.py", "test_probe.py", "fixed_oracle.py"):
                (directory / filename).write_bytes((ROOT / filename).read_bytes())
            (directory / "probe.py").write_text(changed)
            proc = subprocess.run([sys.executable, "-B"] + (["-O"] if sys.flags.optimize else []) + ["test_probe.py"], cwd=directory,
                                  text=True, capture_output=True, timeout=30)
        failures = sorted(set(re.findall(r"^(?:FAIL|ERROR): (test_[A-Za-z0-9_]+)",
                                        proc.stderr, re.MULTILINE)))
        detected = proc.returncode != 0 and required_failure in failures
        results.append({"mutant": name, "old_source": old, "new_source": new,
                        "mutated_probe_sha256": hashlib.sha256(changed.encode()).hexdigest(),
                        "test_exit_code": proc.returncode,
                        "failed_named_tests": failures, "detected": detected})
        if not detected:
            raise AssertionError(json.dumps(results[-1]))
    return {"source_mutants_executed": len(results), "all_detected": True,
            "baseline_probe_sha256": hashlib.sha256(original.encode()).hexdigest(),
            "mutants": results}


if __name__ == "__main__":
    print(json.dumps(run(), ensure_ascii=False, indent=2))

{
  "python": "3.12.14",
  "input_kind": "original authored scores and ranked lists; no retrieval/model run",
  "policy": "one logical route; globally order its supplied comparable candidates",
  "input_batches": [
    {
      "partition": "partition_a",
      "score_contract": "authored-score-v1/same-query/same-snapshot/higher-is-better",
      "hits": [
        {
          "doc_id": "a",
          "score": "0.81"
        },
        {
          "doc_id": "b",
          "score": "0.79"
        },
        {
          "doc_id": "c",
          "score": "0.77"
        }
      ]
    },
    {
      "partition": "partition_b",
      "score_contract": "authored-score-v1/same-query/same-snapshot/higher-is-better",
      "hits": [
        {
          "doc_id": "target",
          "score": "0.96"
        }
      ]
    }
  ],
  "second_route": [
    "target",
    "a",
    "b",
    "c"
  ],
  "parameters": {
    "k": 60,
    "window": 4,
    "size": 4,
    "top1_size": 1
  },
  "cases": [
    {
      "arrival": [
        "partition_a",
        "partition_b"
      ],
      "naive_route": [
        "a",
        "b",
        "c",
        "target"
      ],
      "naive_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "a",
            "b",
            "c",
            "target"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "a",
            "exact_score": "123/3782",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "target",
            "exact_score": "125/3904",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "b",
            "exact_score": "125/3906",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "127/4032",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 4
            }
          }
        ]
      },
      "merged_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "merged_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      },
      "naive_top1": "a",
      "merged_top1": "target"
    },
    {
      "arrival": [
        "partition_b",
        "partition_a"
      ],
      "naive_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "naive_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      },
      "merged_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "merged_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      },
      "naive_top1": "target",
      "merged_top1": "target"
    }
  ],
  "permutation_results": [
    {
      "arrival": [
        "partition_a",
        "partition_b"
      ],
      "a_internal_order": [
        "a",
        "b",
        "c"
      ],
      "naive_route": [
        "a",
        "b",
        "c",
        "target"
      ],
      "naive_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "a",
            "b",
            "c",
            "target"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "a",
            "exact_score": "123/3782",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "target",
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            }
          },
          {
            "doc_id": "c",
            "exact_score": "63/1984",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 4
            }
          },
          {
            "doc_id": "b",
            "exact_score": "127/4032",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 3
            }
          }
        ]
      },
      "merged_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "merged_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      }
    },
    {
      "arrival": [
        "partition_a",
        "partition_b"
      ],
      "a_internal_order": [
        "c",
        "b",
        "a"
      ],
      "naive_route": [
        "c",
        "b",
        "a",
        "target"
      ],
      "naive_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "c",
            "b",
            "a",
            "target"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "c",
            "exact_score": "125/3904",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 4
            }
          },
          {
            "doc_id": "target",
            "exact_score": "125/3904",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "125/3906",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "125/3906",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 3
            }
          }
        ]
      },
      "merged_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "merged_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      }
    },
    {
      "arrival": [
        "partition_b",
        "partition_a"
      ],
      "a_internal_order": [
        "c",
        "b",
        "a"
      ],
      "naive_route": [
        "target",
        "c",
        "b",
        "a"
      ],
      "naive_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "c",
            "b",
            "a"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "63/1984",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "c",
            "exact_score": "63/1984",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 4
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          }
        ]
      },
      "merged_route": [
        "target",
        "a",
        "b",
        "c"
      ],
      "merged_fusion": {
        "candidates": {
          "partitioned_fixture": [
            "target",
            "a",
            "b",
            "c"
          ],
          "second_fixture": [
            "target",
            "a",
            "b",
            "c"
          ]
        },
        "hits": [
          {
            "doc_id": "target",
            "exact_score": "2/61",
            "ranks": {
              "partitioned_fixture": 1,
              "second_fixture": 1
            }
          },
          {
            "doc_id": "a",
            "exact_score": "1/31",
            "ranks": {
              "partitioned_fixture": 2,
              "second_fixture": 2
            }
          },
          {
            "doc_id": "b",
            "exact_score": "2/63",
            "ranks": {
              "partitioned_fixture": 3,
              "second_fixture": 3
            }
          },
          {
            "doc_id": "c",
            "exact_score": "1/32",
            "ranks": {
              "partitioned_fixture": 4,
              "second_fixture": 4
            }
          }
        ]
      }
    }
  ],
  "permutations_checked": 12,
  "single_sorted_batch": {
    "arrival": [
      "a",
      "b",
      "c"
    ],
    "merged": [
      "a",
      "b",
      "c"
    ]
  },
  "cut_before_merge": {
    "kept_ids": [
      "a",
      "b",
      "c"
    ],
    "target_in_first_route": false,
    "target_still_in_second_route": true,
    "fusion_after_lost_first_route_contribution": {
      "candidates": {
        "partitioned_fixture": [
          "a",
          "b",
          "c"
        ],
        "second_fixture": [
          "target",
          "a",
          "b",
          "c"
        ]
      },
      "hits": [
        {
          "doc_id": "a",
          "exact_score": "123/3782",
          "ranks": {
            "partitioned_fixture": 1,
            "second_fixture": 2
          }
        },
        {
          "doc_id": "b",
          "exact_score": "125/3906",
          "ranks": {
            "partitioned_fixture": 2,
            "second_fixture": 3
          }
        },
        {
          "doc_id": "c",
          "exact_score": "127/4032",
          "ranks": {
            "partitioned_fixture": 3,
            "second_fixture": 4
          }
        },
        {
          "doc_id": "target",
          "exact_score": "1/61",
          "ranks": {
            "second_fixture": 1
          }
        }
      ]
    },
    "warning": "second route may still retrieve target; missing first-route evidence is not restored"
  },
  "merge_then_route_window_1": {
    "candidates": {
      "partitioned_fixture": [
        "target"
      ],
      "second_fixture": [
        "target"
      ]
    },
    "hits": [
      {
        "doc_id": "target",
        "exact_score": "2/61",
        "ranks": {
          "partitioned_fixture": 1,
          "second_fixture": 1
        }
      }
    ]
  },
  "naive_then_route_window_1": {
    "candidates": {
      "partitioned_fixture": [
        "a"
      ],
      "second_fixture": [
        "target"
      ]
    },
    "hits": [
      {
        "doc_id": "a",
        "exact_score": "1/61",
        "ranks": {
          "partitioned_fixture": 1
        }
      }
    ]
  },
  "limits": [
    "Same-contract label is only a declared fixture assumption, not proof of comparable real scores",
    "Never sort unrelated BM25 and vector scores together",
    "Separate-list RRF is another valid design with different semantics; not implemented here",
    "No async scheduler, WeKnora deployment, Elasticsearch instance, embeddings, ANN or reranker tested",
    "Only supplied candidates are ordered; missing candidates are not recovered"
  ]
}

{
  "literal_oracle_passed": true,
  "permutations_checked": 12,
  "bad": {
    "candidates": {
      "partitioned_fixture": [
        "a",
        "b",
        "c",
        "target"
      ],
      "second_fixture": [
        "target",
        "a",
        "b",
        "c"
      ]
    },
    "hits": [
      {
        "doc_id": "a",
        "exact_score": "123/3782",
        "ranks": {
          "partitioned_fixture": 1,
          "second_fixture": 2
        }
      },
      {
        "doc_id": "target",
        "exact_score": "125/3904",
        "ranks": {
          "partitioned_fixture": 4,
          "second_fixture": 1
        }
      },
      {
        "doc_id": "b",
        "exact_score": "125/3906",
        "ranks": {
          "partitioned_fixture": 2,
          "second_fixture": 3
        }
      },
      {
        "doc_id": "c",
        "exact_score": "127/4032",
        "ranks": {
          "partitioned_fixture": 3,
          "second_fixture": 4
        }
      }
    ]
  },
  "good": {
    "candidates": {
      "partitioned_fixture": [
        "target",
        "a",
        "b",
        "c"
      ],
      "second_fixture": [
        "target",
        "a",
        "b",
        "c"
      ]
    },
    "hits": [
      {
        "doc_id": "target",
        "exact_score": "2/61",
        "ranks": {
          "partitioned_fixture": 1,
          "second_fixture": 1
        }
      },
      {
        "doc_id": "a",
        "exact_score": "1/31",
        "ranks": {
          "partitioned_fixture": 2,
          "second_fixture": 2
        }
      },
      {
        "doc_id": "b",
        "exact_score": "2/63",
        "ranks": {
          "partitioned_fixture": 3,
          "second_fixture": 3
        }
      },
      {
        "doc_id": "c",
        "exact_score": "1/32",
        "ranks": {
          "partitioned_fixture": 4,
          "second_fixture": 4
        }
      }
    ]
  }
}

{
  "source_mutants_executed": 7,
  "all_detected": true,
  "baseline_probe_sha256": "23477c3e48d340eb27eb3fc456465f4c89eb1b8a900d52fb85f5efbc5e65a1e0",
  "mutants": [
    {
      "mutant": "arrival_as_rank",
      "old_source": "sorted(rows, key=lambda h: (h.score.copy_negate(), h.doc_id))",
      "new_source": "rows",
      "mutated_probe_sha256": "9f4aa9e951af000675b3d4304635652c4e5a703be8623a17db3d70f120821470",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_all_12_fixture_permutations_preserve_correct_fusion",
        "test_empty_batch_and_no_mutation",
        "test_exact_contributions_explain_flip",
        "test_exact_decimal_order_and_stable_ties",
        "test_local_sorted_batches_are_not_global_sorted",
        "test_report_is_deterministic",
        "test_route_window_and_display_size_remain_distinct"
      ],
      "detected": true
    },
    {
      "mutant": "wrong_score_direction",
      "old_source": "(h.score.copy_negate(), h.doc_id)",
      "new_source": "(h.score, h.doc_id)",
      "mutated_probe_sha256": "39c027932d350d61468e982df4de99f440f3f5ab1761e67508506ff245145800",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_all_12_fixture_permutations_preserve_correct_fusion",
        "test_empty_batch_and_no_mutation",
        "test_exact_contributions_explain_flip",
        "test_exact_decimal_order_and_stable_ties",
        "test_local_sorted_batches_are_not_global_sorted",
        "test_report_is_deterministic",
        "test_route_window_and_display_size_remain_distinct",
        "test_single_sorted_batch_is_noop"
      ],
      "detected": true
    },
    {
      "mutant": "unstable_equal_scores",
      "old_source": "(h.score.copy_negate(), h.doc_id)",
      "new_source": "(h.score.copy_negate(),)",
      "mutated_probe_sha256": "1ffeabb6f585882518501e4b63872b4c4faac0136b89caa81b6212e726caae2f",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_exact_decimal_order_and_stable_ties"
      ],
      "detected": true
    },
    {
      "mutant": "skip_score_contract",
      "old_source": "if batch.score_contract != expected_contract:",
      "new_source": "if False:",
      "mutated_probe_sha256": "94ac914d1f70b98771fae67700d6396f906a3daf92eb9abfc5ea5daa53a06070",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_other_score_contract_is_rejected"
      ],
      "detected": true
    },
    {
      "mutant": "cut_before_ordering",
      "old_source": "sorted(rows, key=lambda h: (h.score.copy_negate(), h.doc_id))",
      "new_source": "sorted(rows[:3], key=lambda h: (h.score.copy_negate(), h.doc_id))",
      "mutated_probe_sha256": "8c132a7513135726b334543ca4e44c4a6861b644c44f25a39e0d55a0f068da6b",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_all_12_fixture_permutations_preserve_correct_fusion",
        "test_empty_batch_and_no_mutation",
        "test_exact_contributions_explain_flip",
        "test_local_sorted_batches_are_not_global_sorted",
        "test_report_is_deterministic",
        "test_route_window_and_display_size_remain_distinct"
      ],
      "detected": true
    },
    {
      "mutant": "rounded_decimal_key",
      "old_source": "(h.score.copy_negate(), h.doc_id)",
      "new_source": "(-h.score, h.doc_id)",
      "mutated_probe_sha256": "7d50975a39aa0cd194a25dbae9ee6da224ec7b667eff319918188d046c2ec49d",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_exact_decimal_order_and_stable_ties"
      ],
      "detected": true
    },
    {
      "mutant": "changed_rrf_constant",
      "old_source": "DOCS, {}, k=60, window=window, size=size)",
      "new_source": "DOCS, {}, k=61, window=window, size=size)",
      "mutated_probe_sha256": "d81a9baba863c956cfa9ef5fe87e85563d3c382cd2b5a3f07a2399e51d756686",
      "test_exit_code": 1,
      "failed_named_tests": [
        "test_all_12_fixture_permutations_preserve_correct_fusion",
        "test_early_cut_cannot_restore_missing_route_evidence",
        "test_exact_contributions_explain_flip",
        "test_only_arrival_order_changes_naive_top1",
        "test_route_window_and_display_size_remain_distinct"
      ],
      "detected": true
    }
  ]
}