feat(obligation): obligation-level aggregation engine
Erste Ausführung des Legal Obligation Layer v1: aggregiert Bewertungen auf Kriterium-/Control-Ebene zu Findings auf Obligation-Ebene (Regulation → Legal Obligation → Control → Criterion). - regulierungs-agnostisch (obligation_id/tier/met/legal_basis/conditional) - fail-safe: LM applicable=false→NA · keine erfüllt→FAILED · alle→MET · Teil→PARTIAL; BP/OPT covered→MET sonst OPEN (nie FAILED); LM unbewertbar→UNDETERMINED (Legacy behalten) - Redundanz-Kollaps per OR pro legal_basis-Anforderung → kein künstliches PARTIAL - Applicability als Hook (Prädikat-Engine folgt separat) Shadow-Benchmark (Opus-GT, 3 Firmen): 38 Control-Findings → 13 Obligation-Findings (2,9×); ~23 redundante Falsch-Positive strukturell korrigiert, echte Lücken erhalten, PARTIAL=0. 16/16 Unit-Tests grün. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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"""Obligation Aggregation Engine — Ausführung des Legal Obligation Layer v1.
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Aggregiert Bewertungen auf KRITERIUM-Ebene (pro Control) zu Ergebnissen auf
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OBLIGATION-Ebene. Das ist die erstmalige Ausführung des Modells
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Regulation → Legal Obligation → Control → Criterion
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— das Finding entsteht auf der OBLIGATION, nicht pro Control. Damit kollabiert
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die im Katalog gemessene Redundanz (portability 11×, recipients 14×): N Controls,
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die dieselbe Pflicht prüfen, ergeben EIN Obligation-Finding statt N Control-Findings.
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Regulierungs-agnostisch: kennt nur obligation_id, tier, met, legal_basis,
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conditional. DSGVO/CRA/NIS2/DORA/MaschVO/AI-Act speisen dieselbe Funktion.
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Fail-safe (docs-src/development/legal_obligation_layer_v1.md, §Aggregation):
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LEGAL_MINIMUM-Obligation:
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applicable=false → NA (kein Finding)
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keine LM-Anforderung erfüllt → FAILED (Pflicht-Lücke)
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alle LM-Anforderungen erfüllt → MET
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nur ein Teil erfüllt → PARTIAL
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LM nicht bewertbar (Prüfer down) → UNDETERMINED (Aufrufer behält Legacy)
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BEST_PRACTICE/OPTIONAL-Obligation (kein LM):
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mind. ein Kriterium erfüllt → MET (abgedeckt)
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keines → OPEN (nur Empfehlung, NIE FAILED)
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Redundanz-Kollaps: LM-Kriterien EINER Obligation werden zu „Anforderungen" nach
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`legal_basis` gruppiert; eine Anforderung gilt als erfüllt, sobald IRGENDEIN Control
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sie bestätigt (OR). 9× recipients_disclosed (alle Art 13(1)(e)) = eine Anforderung.
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PARTIAL entsteht nur bei mehreren DISTINKTEN LM-Anforderungen (verschiedene
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legal_basis) innerhalb einer Obligation.
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"""
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from __future__ import annotations
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from collections import Counter, defaultdict
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from dataclasses import dataclass, field
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from typing import Callable, Optional
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LM, BP, OPT = "LEGAL_MINIMUM", "BEST_PRACTICE", "OPTIONAL"
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MET, PARTIAL, FAILED = "MET", "PARTIAL", "FAILED"
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NA, UNDETERMINED, OPEN = "NA", "UNDETERMINED", "OPEN"
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PFLICHT, EMPFEHLUNG, NICHT_ANWENDBAR = "PFLICHT", "EMPFEHLUNG", "NICHT_ANWENDBAR"
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# Predikat-Hook: (conditional, doc_text) → True (anwendbar) / False (→ NA) / None (unbekannt → anwendbar)
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ApplicableFn = Callable[[str, str], Optional[bool]]
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@dataclass(frozen=True)
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class CriterionEval:
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"""Eine Kriteriums-Bewertung eines Controls, einer Obligation zugeordnet."""
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obligation_id: str
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tier: str # LEGAL_MINIMUM / BEST_PRACTICE / OPTIONAL
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met: Optional[bool] # True erfüllt · False fehlt · None unbestimmt
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control_id: str
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legal_basis: str = ""
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criterion: str = ""
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conditional: Optional[str] = None # Applicability-Prädikat der Obligation
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@dataclass
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class ObligationResult:
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obligation_id: str
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status: str # MET / PARTIAL / FAILED / NA / UNDETERMINED / OPEN
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bucket: str # PFLICHT / EMPFEHLUNG / NICHT_ANWENDBAR
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tier: str # bestimmende Tier der Obligation
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applicable: bool
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evidence: list[str] # beitragende control_ids
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lm_met: int # erfüllte LM-Anforderungen
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lm_total: int # distinkte LM-Anforderungen (bewertbar)
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recommendations: list[dict] = field(default_factory=list)
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def _governing_tier(evals: list[CriterionEval]) -> str:
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tiers = {e.tier for e in evals}
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if LM in tiers:
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return LM
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return BP if BP in tiers else OPT
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def _requirement_state(evals: list[CriterionEval]) -> Optional[bool]:
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"""Zustand EINER LM-Anforderung über alle prüfenden Controls (OR/Redundanz):
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True (irgendwer bestätigt) · None (alle unbestimmt) · False (bewertet, fehlt)."""
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if any(e.met is True for e in evals):
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return True
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if all(e.met is None for e in evals):
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return None
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return False
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def _recommendations(evals: list[CriterionEval]) -> list[dict]:
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"""Nicht erfüllte BEST_PRACTICE/OPTIONAL-Kriterien → Empfehlungen."""
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return [{"criterion": e.criterion, "tier": e.tier, "legal_basis": e.legal_basis,
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"control_id": e.control_id}
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for e in evals if e.tier in (BP, OPT) and e.met is False]
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def aggregate_obligation(obligation_id: str, evals: list[CriterionEval], *,
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applicable_fn: Optional[ApplicableFn] = None,
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doc_text: str = "") -> ObligationResult:
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evidence = sorted({e.control_id for e in evals if e.control_id})
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conditional = next((e.conditional for e in evals if e.conditional), None)
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tier = _governing_tier(evals)
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recs = _recommendations(evals)
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applicable = True
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if applicable_fn is not None and conditional:
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verdict = applicable_fn(conditional, doc_text)
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applicable = True if verdict is None else bool(verdict)
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if not applicable:
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return ObligationResult(obligation_id, NA, NICHT_ANWENDBAR, tier, False,
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evidence, 0, 0, recs)
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lm_evals = [e for e in evals if e.tier == LM]
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if lm_evals:
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reqs: dict[str, list[CriterionEval]] = defaultdict(list)
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for e in lm_evals:
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reqs[e.legal_basis or obligation_id].append(e)
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states = [_requirement_state(v) for v in reqs.values()]
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determinable = [s for s in states if s is not None]
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if not determinable:
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return ObligationResult(obligation_id, UNDETERMINED, PFLICHT, LM, True,
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evidence, 0, len(states), recs)
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met = sum(1 for s in determinable if s)
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total = len(determinable)
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status = MET if met == total else (FAILED if met == 0 else PARTIAL)
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return ObligationResult(obligation_id, status, PFLICHT, LM, True,
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evidence, met, total, recs)
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# Reine BEST_PRACTICE/OPTIONAL-Obligation: nie Pflicht, nie FAILED.
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covered = any(e.met is True for e in evals)
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return ObligationResult(obligation_id, MET if covered else OPEN, EMPFEHLUNG,
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tier, True, evidence, 0, 0, recs)
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def aggregate_obligations(evals: list[CriterionEval], *,
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applicable_fn: Optional[ApplicableFn] = None,
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doc_text: str = "") -> list[ObligationResult]:
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"""Flache Kriteriums-Liste → ein ObligationResult je obligation_id."""
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groups: dict[str, list[CriterionEval]] = defaultdict(list)
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for e in evals:
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if e.obligation_id:
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groups[e.obligation_id].append(e)
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return [aggregate_obligation(oid, g, applicable_fn=applicable_fn, doc_text=doc_text)
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for oid, g in groups.items()]
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def evals_from_tiered(control_id: str, tiered_criteria: list[dict],
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detail: list[dict], conditional: Optional[str] = None
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) -> list[CriterionEval]:
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"""Adapter: tiered_criteria (obligation_id/tier/legal_basis) + das
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evaluate_tiered-`detail` (met pro Index, gleiche Reihenfolge) → CriterionEvals.
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`conditional` kommt aus der Control-`applicability` (gilt für die Obligation)."""
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out: list[CriterionEval] = []
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for i, c in enumerate(tiered_criteria or []):
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oid = c.get("obligation_id")
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if not oid:
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continue
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d = detail[i] if i < len(detail) else {}
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out.append(CriterionEval(
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obligation_id=oid,
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tier=(c.get("compliance_tier") or "").upper(),
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met=d.get("met"),
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control_id=control_id,
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legal_basis=c.get("legal_basis") or "",
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criterion=c.get("criterion") or "",
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conditional=conditional,
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))
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return out
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def summarize(results: list[ObligationResult]) -> dict:
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"""Phase-C-Kennzahlen: Obligation-Anzahl + Verteilung nach Bucket/Status."""
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return {
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"obligations": len(results),
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"buckets": dict(Counter(r.bucket for r in results)),
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"statuses": dict(Counter(r.status for r in results)),
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"pflicht_failed": sum(1 for r in results if r.bucket == PFLICHT and r.status == FAILED),
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"pflicht_partial": sum(1 for r in results if r.bucket == PFLICHT and r.status == PARTIAL),
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"recommendations": sum(len(r.recommendations) for r in results),
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}
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"""Unit-Tests Obligation Aggregation Engine (Legal Obligation Layer v1).
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Deckt die fail-safe Regeln + den Redundanz-Kollaps ab (echte DSE-Szenarien:
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recipients 9×, objection LM+BP, portability OPTIONAL-Format)."""
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from compliance.services.obligation_aggregation import (
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BP, LM, OPT, CriterionEval, aggregate_obligation, aggregate_obligations,
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evals_from_tiered, summarize,
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)
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def _ce(oid, tier, met, cid, basis="", crit="", cond=None):
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return CriterionEval(oid, tier, met, cid, basis, crit, cond)
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class TestRedundancyCollapse:
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def test_nine_controls_one_confirms_collapses_to_one_met(self):
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# recipients_disclosed: 9 Controls, gleiche Anforderung (Art 13(1)(e))
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evals = [_ce("recipients_disclosed", LM, i == 4, f"DATA-{i}", "Art. 13(1)(e)")
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for i in range(9)]
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res = aggregate_obligation("recipients_disclosed", evals)
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assert res.status == "MET"
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assert res.lm_met == 1 and res.lm_total == 1 # 9 → 1 Anforderung
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assert len(res.evidence) == 9
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def test_all_nine_absent_fails_once(self):
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evals = [_ce("recipients_disclosed", LM, False, f"DATA-{i}", "Art. 13(1)(e)")
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for i in range(9)]
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res = aggregate_obligation("recipients_disclosed", evals)
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assert res.status == "FAILED"
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assert res.bucket == "PFLICHT"
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class TestPartialMultiFacet:
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def test_two_distinct_lm_requirements_one_met_is_partial(self):
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evals = [
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_ce("transfer", LM, True, "C1", "Art. 13(1)(f)"), # erfüllt
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_ce("transfer", LM, False, "C2", "Art. 46"), # fehlt → distinkt
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]
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res = aggregate_obligation("transfer", evals)
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assert res.status == "PARTIAL"
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assert res.lm_met == 1 and res.lm_total == 2
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def test_both_distinct_requirements_met(self):
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evals = [
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_ce("transfer", LM, True, "C1", "Art. 13(1)(f)"),
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_ce("transfer", LM, True, "C2", "Art. 46"),
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]
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assert aggregate_obligation("transfer", evals).status == "MET"
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class TestApplicability:
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def test_conditional_false_is_na(self):
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evals = [_ce("transfer", LM, False, "C1", "Art. 44", cond="has_third_country_transfer")]
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res = aggregate_obligation("transfer", evals, applicable_fn=lambda c, t: False)
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assert res.status == "NA"
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assert res.bucket == "NICHT_ANWENDBAR"
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assert res.applicable is False
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def test_conditional_true_evaluates_normally(self):
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evals = [_ce("transfer", LM, False, "C1", "Art. 44", cond="has_third_country_transfer")]
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res = aggregate_obligation("transfer", evals, applicable_fn=lambda c, t: True)
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assert res.status == "FAILED"
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def test_conditional_unknown_defaults_applicable(self):
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evals = [_ce("transfer", LM, True, "C1", "Art. 44", cond="x")]
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res = aggregate_obligation("transfer", evals, applicable_fn=lambda c, t: None)
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assert res.applicable is True and res.status == "MET"
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def test_no_predicate_means_applicable(self):
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evals = [_ce("transfer", LM, True, "C1", cond="x")]
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assert aggregate_obligation("transfer", evals).applicable is True
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class TestUndetermined:
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def test_all_lm_none_is_undetermined(self):
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evals = [_ce("ob", LM, None, "C1", "b"), _ce("ob", LM, None, "C2", "b")]
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res = aggregate_obligation("ob", evals)
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assert res.status == "UNDETERMINED"
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assert res.bucket == "PFLICHT"
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def test_one_determinable_requirement_decides(self):
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# eine Anforderung unbestimmt, die andere klar erfüllt → MET über die bewertbare
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evals = [_ce("ob", LM, None, "C1", "b1"), _ce("ob", LM, True, "C2", "b2")]
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res = aggregate_obligation("ob", evals)
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assert res.status == "MET"
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assert res.lm_total == 1 # nur die bewertbare Anforderung zählt
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class TestBestPracticeOnly:
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def test_pure_bp_covered_is_met_recommendation_bucket(self):
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evals = [_ce("art20_format", OPT, True, "C1")]
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res = aggregate_obligation("art20_format", evals)
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assert res.status == "MET"
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assert res.bucket == "EMPFEHLUNG"
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def test_pure_bp_not_covered_is_open_never_failed(self):
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evals = [_ce("art20_format", OPT, False, "C1", crit="JSON/CSV")]
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res = aggregate_obligation("art20_format", evals)
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assert res.status == "OPEN"
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assert res.bucket == "EMPFEHLUNG"
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assert len(res.recommendations) == 1
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class TestRecommendationsWithinLm:
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def test_unmet_bp_in_lm_obligation_becomes_recommendation(self):
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# objection_direct_marketing: LM erfüllt + 3 BP teils offen
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evals = [
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_ce("obj_dm", LM, True, "SEC-8410", "Art. 21(2)", "Recht"),
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_ce("obj_dm", BP, False, "SEC-8410", "", "Kontaktweg"),
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_ce("obj_dm", BP, True, "SEC-8410", "", "kostenlos"),
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]
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res = aggregate_obligation("obj_dm", evals)
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assert res.status == "MET" and res.bucket == "PFLICHT"
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assert len(res.recommendations) == 1
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assert res.recommendations[0]["criterion"] == "Kontaktweg"
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class TestAdapterAndSummary:
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def test_evals_from_tiered_zips_and_skips_no_obligation(self):
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tc = [
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{"criterion": "Recht", "compliance_tier": "LEGAL_MINIMUM",
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"legal_basis": "Art. 21(1)", "obligation_id": "obj_gen"},
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{"criterion": "Weg", "compliance_tier": "BEST_PRACTICE",
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"legal_basis": "", "obligation_id": "obj_gen"},
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{"criterion": "ohne", "compliance_tier": "OPTIONAL"}, # kein obligation_id → skip
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]
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detail = [{"met": True}, {"met": False}, {"met": True}]
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evals = evals_from_tiered("AUTH-2051", tc, detail, conditional="x")
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assert len(evals) == 2
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assert evals[0].met is True and evals[0].conditional == "x"
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assert evals[1].tier == BP and evals[1].met is False
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def test_aggregate_obligations_groups_by_id(self):
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evals = [
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_ce("a", LM, True, "C1", "b"),
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_ce("a", LM, True, "C2", "b"),
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_ce("b", LM, False, "C3", "b"),
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]
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results = {r.obligation_id: r for r in aggregate_obligations(evals)}
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assert set(results) == {"a", "b"}
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assert results["a"].status == "MET"
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assert results["b"].status == "FAILED"
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def test_summarize_counts_buckets_and_failures(self):
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evals = [
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_ce("a", LM, False, "C1", "b"), # FAILED Pflicht
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_ce("c", OPT, False, "C3", crit="x"), # OPEN Empfehlung
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]
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s = summarize(aggregate_obligations(evals))
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assert s["obligations"] == 2
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assert s["pflicht_failed"] == 1
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assert s["buckets"]["PFLICHT"] == 1
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assert s["buckets"]["EMPFEHLUNG"] == 1
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