{"slug": "k501-aionarc-part-01-codebase-of-the-transition-centric-system", "title": "K501-AIONARC - Part 01 - Codebase of the Transition-Centric System", "summary": "A developer released Part 1 of the K501-AIONARC codebase, the Transition-Centric System, featuring canonical serialization and identity generation utilities. The code includes a strict RFC 8785 JCS engine for deterministic hashing and a graph model for transition-based state management.", "body_md": "Here is Part 1 of the complete Google Gemini interpretation from the first phase of K501-AIONARC codebase, the Transition-Centric System . This first batch contains the fundamental utilities and the core graph models. This version of code is not implemeted or tested jet,\n\nits just a referenz and exploration, a Evolution of the code used in RealDeal Build.\n\n`src/k501/utils/canonical_serialization.py`\n\nPython\n\n```\n\"\"\"\nCanonical Serialization: Strict JCS (RFC 8785) Engine for K501-Aionarc.\nGuarantees mathematically unique byte sequences for deterministic IDs.\n\"\"\"\nimport json\nimport hashlib\nfrom typing import Any\n\ndef canonical_serialize(obj: Any) -> str:\n    \"\"\"\n    Serializes an object to canonical JSON according to RFC 8785 JCS.\n    \"\"\"\n    def _serialize(value: Any) -> str:\n        if value is None:\n            return \"null\"\n        if isinstance(value, bool):\n            return \"true\" if value else \"false\"\n        if isinstance(value, int):\n            return str(value)\n        if isinstance(value, float):\n            # Float normalization: prevents discrepancies between 1 and 1.0\n            if value.is_integer():\n                return str(int(value))\n            return f\"{value:.10f}\".rstrip('0').rstrip('.')\n        if isinstance(value, str):\n            # Standard JSON escaping, forced to UTF-8 plaintext\n            return json.dumps(value, ensure_ascii=False)\n        if isinstance(value, list):\n            return \"[\" + \",\".join(_serialize(item) for item in value) + \"]\"\n        if isinstance(value, dict):\n            # Key sorting strictly by Unicode code-points\n            sorted_keys = sorted(value.keys(), key=lambda k: k.encode('utf-8'))\n            return \"{\" + \",\".join(\n                f'\"{k}\":{_serialize(value[k])}' for k in sorted_keys\n            ) + \"}\"\n        raise TypeError(f\"Invalid data type for canonical serialization: {type(value)}\")\n\n    return _serialize(obj)\n\ndef canonical_hash(obj: Any) -> str:\n    \"\"\"Generates a SHA-256 hash of the canonically serialized object.\"\"\"\n    canonical_str = canonical_serialize(obj)\n    return hashlib.sha256(canonical_str.encode('utf-8')).hexdigest()\n```\n\n`src/k501/utils/identity.py`\n\nPython\n\n```\n\"\"\"\nIdentity Engine: Deterministic ID generation based on Transition truth.\n\"\"\"\nfrom typing import Any, Dict\nfrom .canonical_serialization import canonical_hash\n\ndef generate_transition_id(content: Dict[str, Any]) -> str:\n    \"\"\"\n    Generates a deterministic Transition ID.\n    Format: transition:{sha256_24}\n    \"\"\"\n    hash_value = canonical_hash(content)\n    return f\"transition:{hash_value[:24]}\"\n\ndef generate_state_id_from_transition(\n    transition_id: str, \n    object_type: str, \n    axiom_id: str, \n    namespace: str\n) -> str:\n    \"\"\"\n    Derives the StateObject ID directly from its parent transition.\n    Guarantees that no state can exist without an origin transition.\n    \"\"\"\n    content = {\n        \"transition_id\": transition_id,\n        \"object_type\": object_type.lower(),\n        \"axiom_id\": axiom_id,\n        \"namespace\": namespace,\n    }\n    hash_value = canonical_hash(content)\n    return f\"{object_type.lower()}:{hash_value[:24]}\"\n\ndef generate_edge_id(\n    source_id: str, \n    edge_type: str, \n    target_id: str, \n    attributes: Dict[str, Any]\n) -> str:\n    \"\"\"Generates a deterministic ID for relational graph edges.\"\"\"\n    content = {\n        \"source_id\": source_id,\n        \"edge_type\": edge_type.lower(),\n        \"target_id\": target_id,\n        \"attributes\": attributes,\n    }\n    hash_value = canonical_hash(content)\n    return f\"edge:{hash_value[:24]}\"\n```\n\n`src/k501/graph/models.py`\n\nPython\n\n```\n\"\"\"\nGraph Models: Transition-centric node and edge data structures.\n\"\"\"\nfrom dataclasses import dataclass, field\nfrom datetime import datetime, timezone\nfrom enum import Enum\nfrom typing import Any, Dict, Optional\n\nclass TransitionType(Enum):\n    CREATE = \"create\"\n    FREEZE = \"freeze\"\n    ARCHIVE = \"archive\"\n    SUPERSEDE = \"supersede\"\n    VALIDATE = \"validate\"\n    REJECT = \"reject\"\n    CONTEST = \"contest\"\n    ACCEPT = \"accept\"\n    DERIVE = \"derive\"\n\nclass EdgeType(Enum):\n    DERIVED_FROM = \"derived_from\"\n    ANCESTOR = \"ancestor\"\n    VALIDATED_BY = \"validated_by\"\n    AUDITED_BY = \"audited_by\"\n    BELONGS_TO = \"belongs_to\"\n    REFERENCES = \"references\"\n    SUPERSEDES = \"supersedes\"\n\n@dataclass(frozen=True)\nclass TransitionNode:\n    node_id: str  # Corresponds to transition_id\n    transition_type: TransitionType\n    before_state_id: Optional[str]\n    after_state_id: str\n    timestamp: datetime\n    attributes: Dict[str, Any] = field(default_factory=dict)\n\n    @classmethod\n    def create(\n        cls,\n        transition_id: str,\n        transition_type: TransitionType,\n        before_state_id: Optional[str],\n        after_state_id: str,\n        attributes: Optional[Dict[str, Any]] = None,\n    ) -> \"TransitionNode\":\n        return cls(\n            node_id=transition_id,\n            transition_type=transition_type,\n            before_state_id=before_state_id,\n            after_state_id=after_state_id,\n            timestamp=datetime.now(timezone.utc),\n            attributes=attributes or {},\n        )\n\n    def to_dict(self) -> Dict[str, Any]:\n        return {\n            \"node_id\": self.node_id,\n            \"transition_type\": self.transition_type.value,\n            \"before_state_id\": self.before_state_id,\n            \"after_state_id\": self.after_state_id,\n            \"timestamp\": self.timestamp.isoformat(),\n            \"attributes\": self.attributes,\n        }\n\n@dataclass(frozen=True)\nclass TransitionEdge:\n    source_id: str\n    edge_type: EdgeType\n    target_id: str\n    attributes: Dict[str, Any] = field(default_factory=dict)\n\n    @classmethod\n    def create(\n        cls, \n        source_id: str, \n        edge_type: EdgeType, \n        target_id: str, \n        attributes: Optional[Dict[str, Any]] = None\n    ) -> \"TransitionEdge\":\n        return cls(\n            source_id=source_id, \n            edge_type=edge_type, \n            target_id=target_id, \n            attributes=attributes or {}\n        )\n\n    def to_dict(self) -> Dict[str, Any]:\n        return {\n            \"source_id\": self.source_id,\n            \"edge_type\": self.edge_type.value,\n            \"target_id\": self.target_id,\n            \"attributes\": self.attributes,\n        }\n```\n\n`src/k501/graph/store.py`\n\nPython\n\n```\n\"\"\"\nProvenance Graph Store: SQLite persistence and traversal queries.\nOperates on the Transition-Centric model.\n\"\"\"\nimport json\nimport sqlite3\nfrom datetime import datetime, timezone\nfrom pathlib import Path\nfrom typing import Any, Dict, List, Optional\nfrom .models import TransitionNode, TransitionEdge, TransitionType, EdgeType\n\nclass ProvenanceGraph:\n    def __init__(self, db_path: str = \"data/graph/graph.sqlite\"):\n        self.db_path = Path(db_path)\n        self.db_path.parent.mkdir(parents=True, exist_ok=True)\n        self._init_db()\n\n    def _init_db(self) -> None:\n        \"\"\"Initializes the transition-centric SQLite schema.\"\"\"\n        with sqlite3.connect(str(self.db_path)) as conn:\n            cursor = conn.cursor()\n            # Transition nodes\n            cursor.execute(\"\"\"\n                CREATE TABLE IF NOT EXISTS nodes (\n                    node_id TEXT PRIMARY KEY,\n                    transition_type TEXT NOT NULL,\n                    before_state_id TEXT,\n                    after_state_id TEXT NOT NULL,\n                    timestamp TEXT NOT NULL,\n                    attributes TEXT NOT NULL\n                )\n            \"\"\")\n            # Relational edges\n            cursor.execute(\"\"\"\n                CREATE TABLE IF NOT EXISTS edges (\n                    source_id TEXT NOT NULL,\n                    edge_type TEXT NOT NULL,\n                    target_id TEXT NOT NULL,\n                    attributes TEXT NOT NULL,\n                    PRIMARY KEY (source_id, edge_type, target_id)\n                )\n            \"\"\")\n            # Performance indexes\n            cursor.execute(\"CREATE INDEX IF NOT EXISTS idx_edges_source ON edges(source_id)\")\n            cursor.execute(\"CREATE INDEX IF NOT EXISTS idx_edges_target ON edges(target_id)\")\n            cursor.execute(\"CREATE INDEX IF NOT EXISTS idx_edges_type ON edges(edge_type)\")\n            cursor.execute(\"CREATE INDEX IF NOT EXISTS idx_nodes_after_state ON nodes(after_state_id)\")\n            conn.commit()\n\n    def add_node(self, node: TransitionNode) -> bool:\n        try:\n            with sqlite3.connect(str(self.db_path)) as conn:\n                conn.execute(\"\"\"\n                    INSERT OR REPLACE INTO nodes \n                    (node_id, transition_type, before_state_id, after_state_id, timestamp, attributes)\n                    VALUES (?, ?, ?, ?, ?, ?)\n                \"\"\", (\n                    node.node_id, \n                    node.transition_type.value, \n                    node.before_state_id, \n                    node.after_state_id, \n                    node.timestamp.isoformat(),\n                    json.dumps(node.attributes)\n                ))\n                conn.commit()\n            return True\n        except Exception:\n            return False\n\n    def add_edge(self, edge: TransitionEdge) -> bool:\n        try:\n            with sqlite3.connect(str(self.db_path)) as conn:\n                conn.execute(\"\"\"\n                    INSERT OR REPLACE INTO edges \n                    (source_id, edge_type, target_id, attributes)\n                    VALUES (?, ?, ?, ?)\n                \"\"\", (\n                    edge.source_id, \n                    edge.edge_type.value, \n                    edge.target_id, \n                    json.dumps(edge.attributes)\n                ))\n                conn.commit()\n            return True\n        except Exception:\n            return False\n\n    def get_node(self, node_id: str) -> Optional[TransitionNode]:\n        with sqlite3.connect(str(self.db_path)) as conn:\n            cursor = conn.cursor()\n            cursor.execute(\"\"\"\n                SELECT node_id, transition_type, before_state_id, after_state_id, timestamp, attributes \n                FROM nodes WHERE node_id = ?\n            \"\"\", (node_id,))\n            row = cursor.fetchone()\n\n            if not row:\n                return None\n\n            return TransitionNode(\n                node_id=row[0],\n                transition_type=TransitionType(row[1]),\n                before_state_id=row[2],\n                after_state_id=row[3],\n                timestamp=datetime.fromisoformat(row[4]),\n                attributes=json.loads(row[5])\n            )\n\n    def get_edges(self, node_id: str, direction: str = \"forward\", edge_types: Optional[List[EdgeType]] = None) -> List[TransitionEdge]:\n        query = \"SELECT source_id, edge_type, target_id, attributes FROM edges WHERE \"\n        query += \"source_id = ?\" if direction == \"forward\" else \"target_id = ?\"\n\n        with sqlite3.connect(str(self.db_path)) as conn:\n            cursor = conn.cursor()\n            cursor.execute(query, (node_id,))\n            rows = cursor.fetchall()\n\n        edges = []\n        for row in rows:\n            et = EdgeType(row[1])\n            if edge_types is None or et in edge_types:\n                edges.append(TransitionEdge(\n                    source_id=row[0],\n                    edge_type=et,\n                    target_id=row[2],\n                    attributes=json.loads(row[3])\n                ))\n        return edges\n\n    def traverse(\n        self,\n        start_id: str,\n        edge_types: List[EdgeType],\n        direction: str = \"backward\",\n        depth: int = 10,\n        time_filter: Optional[str] = None\n    ) -> List[str]:\n        \"\"\"Traverses the transition graph.\"\"\"\n        visited = set()\n        result = []\n        current_level = [start_id]\n\n        parsed_time = datetime.fromisoformat(time_filter.replace(\"Z\", \"+00:00\")) if time_filter else None\n\n        for _ in range(depth):\n            if not current_level:\n                break\n            next_level = []\n\n            for node_id in current_level:\n                if node_id in visited:\n                    continue\n\n                if parsed_time:\n                    curr_node = self.get_node(node_id)\n                    if not curr_node or curr_node.timestamp > parsed_time:\n                        continue\n\n                visited.add(node_id)\n                result.append(node_id)\n                edges = self.get_edges(node_id, direction, edge_types)\n\n                for edge in edges:\n                    target = edge.target_id if direction == \"forward\" else edge.source_id\n                    if target not in visited:\n                        next_level.append(target)\n            current_level = next_level\n\n        return result\n\n    def get_state_lineage(self, state_id: str) -> List[str]:\n        \"\"\"Finds all transition IDs that contributed to a state lineage.\"\"\"\n        with sqlite3.connect(str(self.db_path)) as conn:\n            cursor = conn.cursor()\n            # Find the transition that created this state\n            cursor.execute(\"SELECT node_id FROM nodes WHERE after_state_id = ?\", (state_id,))\n            rows = cursor.fetchall()\n\n        if not rows:\n            return []\n\n        start_transition_id = rows[0][0]\n        return self.traverse(\n            start_id=start_transition_id, \n            edge_types=[EdgeType.DERIVED_FROM, EdgeType.ANCESTOR], \n            direction=\"backward\", \n            depth=100\n        )\n```\n\n`src/k501/graph/traverse.py`\n\nPython\n\n```\n\"\"\"\nGraph Traversal Utilities: High-level operations on the transition graph.\n\"\"\"\nfrom typing import List\nfrom .store import ProvenanceGraph\n\ndef lineage_traversal(graph: ProvenanceGraph, state_id: str) -> List[str]:\n    \"\"\"Gets the full causal transition lineage for a given StateObject ID.\"\"\"\n    return graph.get_state_lineage(state_id)\n\ndef ancestry_depth(graph: ProvenanceGraph, state_id: str) -> int:\n    \"\"\"Calculates the length of the ancestry chain.\"\"\"\n    return len(graph.get_state_lineage(state_id))\n\ndef common_ancestors(graph: ProvenanceGraph, state_id_1: str, state_id_2: str) -> List[str]:\n    \"\"\"Finds intersection of transition histories between two states.\"\"\"\n    lineage1 = set(graph.get_state_lineage(state_id_1))\n    lineage2 = set(graph.get_state_lineage(state_id_2))\n    return list(lineage1.intersection(lineage2))\n```\n\n`src/k501/graph/query.py`\n\nPython\n\n```\n\"\"\"\nGraph Query: Specialized queries for searching transition chains.\n\"\"\"\nfrom typing import Any, Dict, List\nfrom .models import EdgeType\nfrom .store import ProvenanceGraph\n\ndef query_lineage(graph: ProvenanceGraph, transition_id: str, max_depth: int = 100) -> List[str]:\n    \"\"\"Queries derivation history starting from a specific transition.\"\"\"\n    return graph.traverse(\n        start_id=transition_id, \n        edge_types=[EdgeType.DERIVED_FROM, EdgeType.ANCESTOR], \n        direction=\"backward\", \n        depth=max_depth\n    )\n\ndef query_provenance_audits(graph: ProvenanceGraph, transition_id: str, max_depth: int = 10) -> Dict[str, List[str]]:\n    \"\"\"Queries the validation and audit history for a specific transition.\"\"\"\n    proofs = graph.traverse(start_id=transition_id, edge_types=[EdgeType.VALIDATED_BY], direction=\"backward\", depth=max_depth)\n    audits = graph.traverse(start_id=transition_id, edge_types=[EdgeType.AUDITED_BY], direction=\"backward\", depth=max_depth)\n    return {\n        \"proofs\": proofs,\n        \"audits\": audits\n    }\n\ndef query_before_time(graph: ProvenanceGraph, transition_id: str, time_anchor: str, max_depth: int = 100) -> List[str]:\n    \"\"\"Queries all ancestor transitions restricted by a temporal boundary.\"\"\"\n    return graph.traverse(\n        start_id=transition_id, \n        edge_types=[EdgeType.DERIVED_FROM, EdgeType.ANCESTOR], \n        direction=\"backward\", \n        depth=max_depth, \n        time_filter=time_anchor\n    )\n```\n\nHere is Part 3 of 3. This final section contains the causal validation engine, the deterministic replay verifier, the package initialization, and the core integration test.\n\n`src/k501/graph/validator.py`\n\nPython\n\n```\n\"\"\"\nTransition-Centric Graph Validator: Enforces causality and DAG invariance.\n\"\"\"\nfrom typing import Any, Dict, List, Set\nfrom .models import TransitionEdge, TransitionNode, EdgeType, TransitionType\n\nclass GraphValidationError:\n    def __init__(self, error_type: str, message: str, details: Dict[str, Any] = None):\n        self.error_type = error_type\n        self.message = message\n        self.details = details or {}\n\n    def to_dict(self) -> Dict[str, Any]:\n        return {\"error_type\": self.error_type, \"message\": self.message, \"details\": self.details}\n\nclass TransitionGraphValidator:\n    def __init__(self, nodes: Dict[str, TransitionNode], edges: List[TransitionEdge]):\n        self.nodes = nodes\n        self.edges = edges\n        self._build_adjacency()\n\n    def _build_adjacency(self) -> None:\n        self.forward_edges: Dict[str, List[TransitionEdge]] = {}\n        self.backward_edges: Dict[str, List[TransitionEdge]] = {}\n        for edge in self.edges:\n            self.forward_edges.setdefault(edge.source_id, []).append(edge)\n            self.backward_edges.setdefault(edge.target_id, []).append(edge)\n\n    def validate(self) -> List[GraphValidationError]:\n        errors = []\n        errors.extend(self.validate_transition_chain())\n        errors.extend(self.validate_dag())\n        return errors\n\n    def validate_transition_chain(self) -> List[GraphValidationError]:\n        errors = []\n        state_transitions: Dict[str, List[TransitionNode]] = {}\n\n        for node in self.nodes.values():\n            state_transitions.setdefault(node.after_state_id, []).append(node)\n\n        for state_id, transitions in state_transitions.items():\n            # Rule 1: Every state needs exactly one origin transition (CREATE)\n            has_create = any(t.transition_type == TransitionType.CREATE for t in transitions)\n            if not has_create:\n                errors.append(GraphValidationError(\n                    \"MISSING_CREATE\", \n                    f\"State {state_id} has no CREATE transition.\"\n                ))\n                continue\n\n            # Rule 2: Enforce chronological integrity of the lifecycle\n            create_ts = next((t.timestamp for t in transitions if t.transition_type == TransitionType.CREATE), None)\n            freeze_ts = next((t.timestamp for t in transitions if t.transition_type == TransitionType.FREEZE), None)\n            archive_ts = next((t.timestamp for t in transitions if t.transition_type == TransitionType.ARCHIVE), None)\n\n            if freeze_ts and create_ts and freeze_ts < create_ts:\n                errors.append(GraphValidationError(\n                    \"CHRONOLOGY_VIOLATION\", \n                    f\"State {state_id}: FREEZE occurs before CREATE.\"\n                ))\n            if archive_ts and freeze_ts and archive_ts < freeze_ts:\n                errors.append(GraphValidationError(\n                    \"CHRONOLOGY_VIOLATION\", \n                    f\"State {state_id}: ARCHIVE occurs before FREEZE.\"\n                ))\n        return errors\n\n    def validate_dag(self) -> List[GraphValidationError]:\n        errors = []\n        derive_adj: Dict[str, List[str]] = {}\n\n        for edge in self.edges:\n            if edge.edge_type == EdgeType.DERIVED_FROM:\n                derive_adj.setdefault(edge.source_id, []).append(edge.target_id)\n\n        visited: Set[str] = set()\n        rec_stack: Set[str] = set()\n\n        def has_cycle(node: str) -> bool:\n            visited.add(node)\n            rec_stack.add(node)\n            for neighbor in derive_adj.get(node, []):\n                if neighbor not in visited:\n                    if has_cycle(neighbor):\n                        return True\n                elif neighbor in rec_stack:\n                    return True\n            rec_stack.remove(node)\n            return False\n\n        for node_id in derive_adj:\n            if node_id not in visited:\n                if has_cycle(node_id):\n                    errors.append(GraphValidationError(\n                        \"CYCLE_DETECTED\", \n                        \"Cyclic dependency detected in DERIVED_FROM edges.\", \n                        {\"node_id\": node_id}\n                    ))\n        return errors\n```\n\n`src/k501/graph/replay_validator.py`\n\nPython\n\n```\n\"\"\"\nReplay Validator: Verifies absolute replay determinism of K501-Aionarc.\n\"\"\"\nfrom typing import Dict, List\nfrom .models import TransitionEdge, TransitionNode\nfrom .validator import GraphValidationError\n\nclass ReplayValidator:\n    def __init__(\n        self,\n        original_nodes: Dict[str, TransitionNode],\n        original_edges: List[TransitionEdge],\n        replayed_nodes: Dict[str, TransitionNode],\n        replayed_edges: List[TransitionEdge],\n    ):\n        self.original_nodes = original_nodes\n        self.original_edges = original_edges\n        self.replayed_nodes = replayed_nodes\n        self.replayed_edges = replayed_edges\n\n    def validate_replay(self) -> List[GraphValidationError]:\n        errors = []\n\n        # 1. Check structural identity of nodes\n        orig_node_ids = set(self.original_nodes.keys())\n        repl_node_ids = set(self.replayed_nodes.keys())\n\n        if orig_node_ids != repl_node_ids:\n            errors.append(GraphValidationError(\n                \"REPLAY_NODE_MISMATCH\", \n                \"Node sets of original and replay do not match.\", \n                {\n                    \"missing_in_replay\": list(orig_node_ids - repl_node_ids),\n                    \"extra_in_replay\": list(repl_node_ids - orig_node_ids)\n                }\n            ))\n\n        # 2. Check structural identity of edges\n        orig_edge_signatures = {(e.source_id, e.edge_type.value, e.target_id) for e in self.original_edges}\n        repl_edge_signatures = {(e.source_id, e.edge_type.value, e.target_id) for e in self.replayed_edges}\n\n        if orig_edge_signatures != repl_edge_signatures:\n            errors.append(GraphValidationError(\n                \"REPLAY_EDGE_MISMATCH\", \n                \"Edge topology differs after replay.\", \n                {\n                    \"missing_edges\": list(orig_edge_signatures - repl_edge_signatures),\n                    \"extra_edges\": list(repl_edge_signatures - orig_edge_signatures)\n                }\n            ))\n\n        # 3. Deep-Comparison of state attributes (Invariance check)\n        for node_id in orig_node_ids.intersection(repl_node_ids):\n            if self.original_nodes[node_id].attributes != self.replayed_nodes[node_id].attributes:\n                errors.append(GraphValidationError(\n                    \"REPLAY_ATTRIBUTE_MUTATION\", \n                    f\"Attribute mutation detected in Node {node_id}.\", \n                    {\n                        \"original\": self.original_nodes[node_id].attributes,\n                        \"replayed\": self.replayed_nodes[node_id].attributes\n                    }\n                ))\n\n        return errors\n\n    def is_identical(self) -> bool:\n        return len(self.validate_replay()) == 0\n```\n\n`src/k501/graph/__init__.py`\n\nPython\n\n``` python\n\"\"\"\nGraph Module Export Hub\n\"\"\"\nfrom .models import TransitionNode, TransitionEdge, TransitionType, EdgeType\nfrom .store import ProvenanceGraph\nfrom .traverse import lineage_traversal, ancestry_depth, common_ancestors\nfrom .query import query_lineage, query_provenance_audits, query_before_time\nfrom .validator import TransitionGraphValidator, GraphValidationError\nfrom .replay_validator import ReplayValidator\n\n__all__ = [\n    \"TransitionNode\",\n    \"TransitionEdge\",\n    \"TransitionType\",\n    \"EdgeType\",\n    \"ProvenanceGraph\",\n    \"lineage_traversal\",\n    \"ancestry_depth\",\n    \"common_ancestors\",\n    \"query_lineage\",\n    \"query_provenance_audits\",\n    \"query_before_time\",\n    \"TransitionGraphValidator\",\n    \"GraphValidationError\",\n    \"ReplayValidator\",\n]\n```\n\n`tests/unit/test_transition_consensus.py`\n\nPython\n\n```\n\"\"\"\nIntegrated Verification Test: Validates RFC 8785 and Causal Topology constraints.\n\"\"\"\nimport pytest\nfrom datetime import datetime, timezone, timedelta\nfrom k501.utils.canonical_serialization import canonical_serialize, canonical_hash\nfrom k501.utils.identity import generate_transition_id, generate_state_id_from_transition\nfrom k501.graph.models import TransitionNode, TransitionEdge, TransitionType, EdgeType\nfrom k501.graph.validator import TransitionGraphValidator\n\ndef test_rfc8785_float_and_dict_determinism():\n    \"\"\"Different memory layouts and data types must yield identical byte strings.\"\"\"\n    dict_a = {\"alpha\": 1.0, \"beta\": [1, 2]}\n    dict_b = {\"beta\": [1, 2], \"alpha\": 1}\n    assert canonical_serialize(dict_a) == canonical_serialize(dict_b)\n\ndef test_causal_lifecycle_chronology():\n    \"\"\"Constructs a corrupt timeline (FREEZE before CREATE) and validates rejection.\"\"\"\n    base_time = datetime.now(timezone.utc)\n\n    t1_content = {\"action\": \"initial_creation\"}\n    t1_id = generate_transition_id(t1_content)\n    s_id = generate_state_id_from_transition(t1_id, \"frame\", \"axiom:0\", \"sys\")\n\n    # Create temporally invalid nodes\n    node_create = TransitionNode(t1_id, TransitionType.CREATE, None, s_id, base_time)\n    node_freeze = TransitionNode(\n        \"transition:fake_freeze\", \n        TransitionType.FREEZE, \n        s_id, \n        s_id, \n        base_time - timedelta(seconds=10) # Time travel anomaly\n    )\n\n    nodes = {node_create.node_id: node_create, node_freeze.node_id: node_freeze}\n    validator = TransitionGraphValidator(nodes, [])\n\n    errors = validator.validate()\n    assert any(err.error_type == \"CHRONOLOGY_VIOLATION\" for err in errors)\nPatrick R. Miller (Iinkognit0) — K501 / AIONARC Core Architecture\nORCID: https://orcid.org/0009-0005-5125-9711\nWebsite: https://iinkognit0.de/\nGitHub: https://github.com/Iinkognit0\nGitHub: https://github.com/k501-Information-Space/eArc\nPublications: https://dev.to/k501is\nMastodon: https://mastodon.social/@K501\nEmail: contact.k501@proton.me\n```\n\nUnix Epoch 1781737019", "url": "https://wpnews.pro/news/k501-aionarc-part-01-codebase-of-the-transition-centric-system", "canonical_source": "https://dev.to/k501is/k501-aionarc-part-01-codebase-of-the-transition-centric-system-2edo", "published_at": "2026-06-17 23:04:02+00:00", "updated_at": "2026-06-17 23:21:18.048433+00:00", "lang": "en", "topics": ["developer-tools", "machine-learning", "artificial-intelligence"], "entities": ["K501-AIONARC", "Google Gemini", "RealDeal Build", "RFC 8785", "SHA-256"], "alternates": {"html": "https://wpnews.pro/news/k501-aionarc-part-01-codebase-of-the-transition-centric-system", "markdown": "https://wpnews.pro/news/k501-aionarc-part-01-codebase-of-the-transition-centric-system.md", "text": "https://wpnews.pro/news/k501-aionarc-part-01-codebase-of-the-transition-centric-system.txt", "jsonld": "https://wpnews.pro/news/k501-aionarc-part-01-codebase-of-the-transition-centric-system.jsonld"}}