Benjamin Admin
ecae5bc7f1
Before the next Journey: the LANGUAGE. With 5 knowledge objects but no vocabulary, the same reise gets named four different ways (ISO9001->MaschinenVO vs Quality Management->Product Safety vs ...). The spec answers ONE question: which terms are IDENTITIES and which are REPRESENTATIONS of the same meaning? - spec docs-src/architecture/domain-vocabulary-spec-v1.md (PROPOSAL): identity hierarchy (Requirement RQ / Capability MCAP [Registry 2C] / regulation-source-target / Journey Class MJRN [PROVISIONAL] / Journey instance / Playbook MPLB); canonical name + aliases; capability vocabulary = the Capability Registry (not rebuilt); reorder Vocabulary -> Transition #2 -> #3 -> Rule of Three. - knowledge/vocabulary/regulations.yaml: regulation/standard IDENTITIES (id + canonical + aliases). SOLVES the regulation-ID normalization the KPIs flagged: CRA == "Cyber Resilience Act" == "Regulation (EU) 2024/2847" all resolve to `cra`; ISO9001/QMS -> iso9001; etc. Shared artifact (@Legal-KG/@Execution please adopt). - knowledge/vocabulary/journey_classes.yaml (PROVISIONAL): clusters our transitions into classes (Information Security -> Product Cybersecurity; Quality Management -> Product Compliance/Safety). Finding: ISO9001->MaschinenVO is an INSTANCE of an existing class (like ISO9001->CRA, ISO13485->MDR), not a new kind -> avoids duplication. Journey Class is a new abstraction -> its own Rule of Three (no MJRN minting yet). - reference suite: both KPIs now read aliases from regulations.yaml instead of hard-coded maps; the "Regelwerk-ID-Normalisierung" line flips TODO -> PASS. KPI numbers unchanged (vocab is a superset). - Side effect = Requirements Intelligence: a Tender "Security Patch Procedure" resolves to MCAP-0017. 7 vocabulary tests (17 with domain programs), check-loc 0. Knowledge data + spec + reference harness = non-runtime -> no deploy (ADR-001). No new module, no runtime change, no minting (Freeze). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
87 lines
3.2 KiB
Python
87 lines
3.2 KiB
Python
"""Characterization tests for the Domain Vocabulary (data, not code).
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Pins the IDENTITY-vs-REPRESENTATION contract: regulations have a stable id + canonical name + aliases
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(so CRA and "Cyber Resilience Act" resolve to the SAME identity — the normalization that the KPIs
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flagged). Journey classes cluster transition instances so we do not duplicate the same reise; they
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are PROVISIONAL (no MJRN minting) and reference regulation ids that exist in the vocabulary.
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"""
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from __future__ import annotations
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import os
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import yaml
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_VOCAB = os.path.join(os.path.dirname(__file__), "..", "knowledge", "vocabulary")
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def _regs():
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with open(os.path.join(_VOCAB, "regulations.yaml"), encoding="utf-8") as h:
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return yaml.safe_load(h)["regulations"]
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def _classes():
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with open(os.path.join(_VOCAB, "journey_classes.yaml"), encoding="utf-8") as h:
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return yaml.safe_load(h)
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def _norm(s):
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return "".join(c for c in str(s).lower() if c.isalnum())
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def _alias_map():
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amap = {}
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for r in _regs():
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for name in [r["canonical"]] + list(r.get("aliases", [])):
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amap[_norm(name)] = r["id"]
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return amap
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def test_every_regulation_has_id_canonical_aliases():
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for r in _regs():
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assert r["id"] and r["canonical"] and r["aliases"]
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assert r["id"] == r["id"].lower() # ids are lowercase stable keys
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def test_cra_spellings_resolve_to_one_identity():
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amap = _alias_map()
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# the exact normalization the KPIs needed: CRA == Cyber Resilience Act
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assert amap[_norm("CRA")] == "cra" and amap[_norm("Cyber Resilience Act")] == "cra"
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assert amap[_norm("Regulation (EU) 2024/2847")] == "cra"
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def test_iso_and_management_system_aliases_resolve():
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amap = _alias_map()
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assert amap[_norm("ISO9001")] == "iso9001" and amap[_norm("QMS")] == "iso9001"
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assert amap[_norm("ISO/IEC 27001")] == "iso27001" and amap[_norm("ISMS")] == "iso27001"
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assert amap[_norm("Maschinenverordnung")] == "maschinenvo" and amap[_norm("MaschinenVO")] == "maschinenvo"
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def test_aliases_are_unambiguous():
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# no normalized alias maps to two different regulation identities
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seen = {}
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for r in _regs():
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for name in [r["canonical"]] + list(r.get("aliases", [])):
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k = _norm(name)
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assert seen.get(k, r["id"]) == r["id"], "ambiguous alias %r" % name
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seen[k] = r["id"]
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def test_journey_classes_are_provisional():
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assert _classes()["status"] == "provisional" # new abstraction -> own Rule of Three
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def test_iso9001_maschinenvo_is_an_instance_not_a_new_kind():
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classes = _classes()["classes"]
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qm = [c for c in classes if c["id"] == "qm-to-product-compliance"][0]
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pairs = {(i["from"], i["to"]) for i in qm["instances"]}
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assert ("iso9001", "maschinenvo") in pairs # same CLASS as iso9001->cra, iso13485->mdr
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assert ("iso13485", "mdr") in pairs # class generalises across domains
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def test_class_endpoints_reference_known_regulations():
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reg_ids = {r["id"] for r in _regs()}
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for c in _classes()["classes"]:
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for inst in c["instances"]:
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assert inst["from"] in reg_ids and inst["to"] in reg_ids # vocabulary is internally consistent
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