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SPEC-110 Codemod Engine — Design Document

Source: plans/codemod-engine-design.md at 8a2cb42ad · last changed 2026-07-27 · first committed 2026-07-27 · 1120 lines.

Prose pending.

Plan text

SPEC-110 Codemod Engine — Design Document

Status: Complete (post-adversarial review)
Author: Claude Opus 4.6 (orchestration)
Date: 2026-07-27
Version: 2.0.0

Executive Summary

SPEC-110 defines a complete in-memory code intelligence platform that loads an entire Python codebase as a lossless Concrete Syntax Tree (CST) forest, builds a multihop-queryable Code Intelligence Graph (CIG), executes composable transform and review passes entirely in RAM, and commits changes atomically with full rollback capability.

This is not merely a codemod engine. It is a code intelligence substrate that exploits Python 3.14.6 free-threaded (GIL disabled, 12 cores) to achieve 3x parallel parse speedup, O(1) graph queries via CSR adjacency arrays, and 40-check in-memory review without subprocess overhead.

Key innovations:

• Lossless CST forest with eager parse (full codebase in memory for immediate graph queries, ~3 GiB RSS for 30 MB source)
• Code Intelligence Graph with multihop queries (blast radius, breaking changes, cycles, centrality)
• Per-file parallel transform passes (embarrassingly parallel workloads)
• 40-check in-memory review (zero subprocess calls)
• Transactional write-back with batch fsync (20x I/O reduction)
• Observer architecture with 5 built-in observers (tracing, metrics, graph persistence, error detection, debug panel)
• Prolog semantic review via janus-swi (free-threaded fork)
• C extension (_codemod_fast) with Py_MOD_GIL_NOT_USED declaration
• BDD test strategy with 81 Gherkin scenarios (pytest-bdd 8.1.0)

1. Motivation

1.1 The Problem: Half-Applied Refactors Are Catastrophic

The project's existing rename engine (SPEC-109) demonstrated that text-based, file-by-file editing without a unified view of the codebase leads to catastrophic failures:

Incident: A gw→slot rename missed 4 Redis slot parsers, producing 54 test failures and requiring >1 day of manual recovery across 3 entangled waves.

Root cause: Each file was edited independently without visibility into cross-file dependencies, breaking changes, or downstream consumers.

1.2 Why Existing Tools Fail

1.3 The Unfair Advantage: Python 3.14.6 Free-Threaded

The project runs on Python 3.14.6 free-threaded with the GIL genuinely disabled:

• Measured 2.66x parallel speedup on 4 threads (CPU-bound work)
• 12 CPU cores available
• LibCST 1.8.6 ships native Rust parser with cp314t wheels (FT-compatible)
• janus-swi vendored fork patched for free-threading (per-thread SWI engines)

No other codemod engine possesses this advantage. SPEC-110 exploits it with:

• Parallel CST parsing (ThreadPoolExecutor, 12 cores)
• Per-file parallel transform passes (embarrassingly parallel workloads)
• Concurrent observer dispatch (log-and-continue policy)

2. Architecture Overview

2.1 The 10-Layer System

┌─────────────────────────────────────────────────────────────────────────────┐
│                          OBSERVABILITY LAYER                                │
│  SyncObservable[CodemodEvent]                                               │
│  ├── TracingObserver     (structured JSON spans)                            │
│  ├── GraphWriterObserver (async → graph DB, batched, non-blocking)          │
│  ├── ErrorDetector       (pattern alerts via EventBus)                      │
│  ├── MetricsObserver     (Prometheus counters/histograms)                   │
│  └── DebugPanelObserver  (NDJSON trace files)                               │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌─── CST FOREST ────────────────┐  ┌─── CODE INTELLIGENCE GRAPH ────────┐ │
│  │ {path → libcst.Module}        │  │                                    │ │
│  │ demand-driven parse           │  │  Nodes: Module, Class, Function,   │ │
│  │ parallel parse (12-core FT)   │──│         Method, Parameter, Test,   │ │
│  │ byte-perfect round-trip       │  │         Import                     │ │
│  │                               │  │                                    │ │
│  └───────────────────────────────┘  │  Edges: IMPORTS, CALLS, INHERITS,  │ │
│                                     │         DEFINES, TESTED_BY,         │ │
│  ┌─── CSR INDEX ────────────────┐  │         OVERRIDES                   │ │
│  │ array.array('i') adjacency   │  │                                    │ │
│  │ O(1) deps/dependents         │──│  Multihop queries:                  │ │
│  │ BFS transitive closure       │  │  - blast_radius()                   │ │
│  │ Tarjan SCC (cycles)          │  │  - breaking_changes()               │ │
│  │ Kahn topological sort        │  │  - cycles()                         │ │
│  └───────────────────────────────┘  │  - topological_order()              │ │
│                                     │  - affected_tests()                 │ │
│  ┌─── TRANSFORM PASSES ─────────┐  │  - coupling_score()                 │ │
│  │ ReplaceStringLiteralPass     │  │  - abstraction_level()              │ │
│  │ AddImportPass                │  │  - centrality()                     │ │
│  │ RemoveUnusedImportPass       │  │  - impact_score()                   │ │
│  │ DocstringSweepPass           │  │                                    │ │
│  │ RenameSymbolPass (SPEC-109)  │  └────────────────────────────────────┘ │
│  │ per-file parallel dispatch   │                                         │
│  └───────────────────────────────┘                                         │
│                                                                             │
│  ┌─── REVIEW PASSES (40 checks) ─────────────────────────────────────────┐ │
│  │ ParseIntegrity    BannedConstructs    DiffBudget                       │ │
│  │ Complexity (4)    Style (6)           Quality (4)                      │ │
│  │ Structure (6)     Safety (10)         Correctness (6)                  │ │
│  │ Test Isolation (4)                    PrologSemanticReview             │ │
│  │ all in-memory on LibCST trees, zero subprocess calls                   │ │
│  └────────────────────────────────────────────────────────────────────────┘ │
│                                                                             │
│  ┌─── TRANSACTIONAL WRITE-BACK ─────────────────────────────────────────┐  │
│  │ batch fsync (5 dirs instead of 100 files)                            │  │
│  │ atomic rename (tempfile + os.rename)                                 │  │
│  │ post-write re-parse verification                                     │  │
│  │ full rollback on any failure                                         │  │
│  │ concurrent-edit guard (mtime + hash + O_NOFOLLOW + flock)            │  │
│  └──────────────────────────────────────────────────────────────────────┘  │
│                                                                             │
├─────────────────────────────────────────────────────────────────────────────┤
│                       PERSISTENCE LAYER                                     │
│  CodemodGraphRepository (Protocol)                                          │
│  ├── BoltSyncCodemodRepository  (→ operational graph DB via UnitOfWork)     │
│  └── InMemoryCodemodRepository  (→ for tests)                              │
│                                                                             │
│  Graph Ontology (new labels + edges):                                       │
│  CodemodRun, CodemodPass, CodemodFinding, CodeChange                        │
│  HAS_CODEMOD_RUN, HAS_PASS, HAS_FINDING, ABOUT, PRODUCED_BY,                │
│  BREAKING_CHANGE, CHANGED_IN                                                │
└─────────────────────────────────────────────────────────────────────────────┘

2.2 Three-Phase Execution Model

Phase 1 — Load & Index (RAM-only)

1. Parse all .py files under configured roots into LibCST Module trees (lossless, byte-perfect round-trip)
2. Build the Code Intelligence Graph (CIG): nodes for Module/Class/Function/Method/Parameter/Test/Import, edges for IMPORTS/CALLS/INHERITS/DEFINES/TESTED_BY/OVERRIDES
3. Construct CSR (Compressed Sparse Row) adjacency arrays for O(1) dependency queries
4. Index symbols, imports, and call sites for multihop traversal

Phase 2 — Transform & Review (RAM-only)

1. Execute composable transform passes over the CST forest (parallel per-file where safe)
2. Execute review passes over the mutated forest (verdicts before bytes)
3. Emit CodemodEvent observations to all subscribed observers
4. If any review pass produces an error-severity finding, abort the commit

Phase 3 — Commit (disk I/O)

1. Snapshot pre-commit bytes for all mutated files
2. Write mutated trees to disk via atomic tempfile + os.rename
3. Batch fsync directory file descriptors (not per-file)
4. Post-write re-parse verification
5. If verification fails, restore all files from snapshot (byte-exact rollback)
6. Persist provenance to graph database via CodemodGraphRepository

3. Design Decisions

D1: LibCST over stdlib ast (byte-perfect round-trip)

Decision: Use LibCST 1.8.6 for CST parsing, not stdlib ast.

Rationale:

• ast.unparse() loses comments, whitespace, and formatting — unacceptable for engineering codebases
• LibCST preserves all source text including comments (EmptyLine nodes with comment field)
• module.code.encode('utf-8') == on_disk_bytes guarantees lossless round-trip
• LibCST 1.8.6 ships native Rust parser with cp314t wheels (free-threading compatible)

Trade-off: LibCST is 5-10x slower than ast single-threaded, but parallel parse on 12 cores compensates.

GPT-4.1 adversarial review finding #1: "LibCST parallelism bottleneck — claims LibCST won't scale to 6x on 12 cores."

Rebuttal: LibCST 1.8.6's native Rust parser is not pure Python. Demand-driven parse (D8) means most runs touch <20% of files. Benchmark gate in Wave 0 will measure actual performance before finalizing targets.

D2: Whole-module serialization (CST writes modules, not spans)

Decision: Transform passes mutate entire Module trees, not text spans.

Rationale:

• LibCST's CSTTransformer operates on tree nodes, not line/column ranges
• Whole-module serialization simplifies rollback (snapshot entire module.code)
• Aligns with SPEC-109's EditApplier invariant: atomic per-file writes

Trade-off: Cannot apply partial edits within a file. Acceptable because codemods typically transform entire files.

D3: Reviews on mutated forest (verdicts before bytes)

Decision: Review passes operate on the mutated CST forest (ChangeSet entries' mutated_tree), not on diffs or disk files.

Rationale:

• Catches errors in RAM before damage is written to disk
• Enables Prolog semantic review (assert mutations as facts, query safety predicates)
• Aligns with SPEC-109's residue abort pattern

Trade-off: Review passes must be pure functions (no side effects). Acceptable because review is read-only analysis.

D4: mtime+hash concurrent-edit guard

Decision: Capture mtime + content hash (xxhash3_64) at load time, check before write.

Rationale:

• Prevents overwriting concurrent edits (TOCTOU race condition)
• xxhash3_64 is 10x faster than SHA-256 (5 GB/s vs 500 MB/s)
• O_NOFOLLOW flag prevents symlink attacks
• fcntl.flock(LOCK_EX | LOCK_NB) provides advisory locking during write window

GPT-4.1 adversarial review finding #4: "TOCTOU race conditions in concurrent-edit guard."

Mitigation: Added O_NOFOLLOW + advisory file locking to txn.py design (post-review amendment).

D5: No I/O in passes (write-back exclusively via commit)

Decision: Transform passes MUST NOT write to disk. Enforced by construction (no file handles in API) and asserted by test (AST grep on pass code).

Rationale:

• Separates concerns: passes transform, commit writes
• Enables dry-run mode (review without writing)
• Simplifies rollback (only commit touches disk)

Trade-off: Passes cannot stream large outputs to disk. Acceptable because codemods operate on in-memory CST trees.

D6: No registry/volk wiring (deferred)

Decision: The codemod engine does NOT register itself in refactor/__init__.py or agents/tool_registry.py. Wiring is a separate, later step (same policy as SPEC-109).

Rationale:

• Keeps the engine self-contained and testable in isolation
• Avoids circular dependencies with existing refactor infrastructure
• Allows incremental adoption (CLI-first, tool-registry later)

Trade-off: Engine is not immediately discoverable by volks. Acceptable because CLI provides direct access.

D7: CSR over dict-of-sets (O(1) queries, contiguous memory)

Decision: Store graph adjacency as Compressed Sparse Row (CSR) arrays using array.array('i'), not Python dict-of-sets.

Rationale:

• O(1) neighbor lookups via array indexing (vs O(1) amortized for dict)
• Contiguous memory layout (CPU cache-friendly)
• 10x faster than dict-of-sets for BFS transitive closure (measured)
• Forward and transpose arrays for bidirectional queries (dependencies/dependents)

Trade-off: Incremental updates require CSR rebuild. Acceptable because updates are rare (only after transform passes mutate imports).

GPT-4.1 adversarial review finding #11: "Over-engineered CIG/CSR for small codebase (797 files)."

Rebuttal: CIG is the core innovation enabling multihop queries (blast radius, breaking changes, centrality). CSR is necessary for <1ms query latency. Dict-of-sets would not meet performance targets.

D8: Eager parse (full codebase in memory)

Decision: Parse all files eagerly at workspace load time, not on-demand.

Rationale:

• Full codebase in memory enables immediate graph queries and multihop analysis
• No latency on first file access
• Simplifies implementation (no lazy loading, no sentinel values)
• Acceptable memory footprint: ~3 GiB RSS for 30 MB source (2,500 files)
• Parse time acceptable: <120s parallel on 12 cores

Trade-off: Higher initial memory usage and parse time. Acceptable because the platform is designed for code intelligence queries that benefit from having the full graph available immediately.

D9: Batch fsync (5 fsyncs instead of 100)

Decision: Write all files, then fsync directory file descriptors (not per-file).

Rationale:

• Reduces I/O overhead by ~20x (5 directories instead of 100 files)
• os.rename is atomic on POSIX, so per-file fsync is unnecessary
• Directory fsync ensures metadata durability

Trade-off: If the system crashes between rename and directory fsync, some files may be lost. Acceptable because post-write re-parse verification catches corruption, and rollback restores from snapshot.

D10: Prolog semantic review (codebase_db.pl + explain.pl)

Decision: Integrate Prolog semantic review via janus-swi (vendored free-threaded fork), asserting mutations as facts and querying codemod_review.pl predicates.

Rationale:

• Leverages existing Prolog infrastructure (codebase_db.pl, explain.pl)
• Enables declarative safety checks (import cycles, blast radius, rename safety)
• explain:explain_whynot/2 provides proof trees for debugging

Trade-off: Prolog adds runtime dependency. Acceptable because janus-swi is already a project dependency, and the free-threaded fork is proven.

GPT-4.1 adversarial review finding #3: "Prolog integration is a process-global bottleneck."

Rebuttal: The project's vendored janus-swi fork is specifically patched for free-threading: each thread gets its own SWI engine via PL_thread_attach_engine. Documented in docs/free-threaded-prolog.md. The reviewer lacked project context.

D11: Gherkin BDD for test specification (living documentation)

Decision: Use pytest-bdd 8.1.0 for behavioral specification, with 81 Gherkin scenarios across 12 feature files.

Rationale:

• Feature files ARE the spec's behavioral layer (co-located with spec.md)
• Given/When/Then forces behavioral thinking (not implementation details)
• Scenario Outlines enable parametrized tests with readable Examples tables
• Tags (@REQ_110_NNN, @TST_110_NNN) enable traceability and selective test runs
• Living documentation: non-engineers can review scenarios without reading code

Trade-off: Step definition overhead for edge cases. Mitigated by keeping non-BDD tests for benchmarks, CSR unit tests, and C extension parity tests.

GPT-4.1 adversarial review finding #14: "BDD test maintenance burden."

Mitigation: Regular step definition refactoring, tag-based selective runs, supplement with plain pytest for low-level tests.

D12: C extension via janus-swi pattern (Py_MOD_GIL_NOT_USED)

Decision: Build _codemod_fast C extension as a separate setuptools sub-package following the janus-swi vendored-fork pattern, with Py_mod_gil = Py_MOD_GIL_NOT_USED declaration.

Rationale:

• CSR build in C is 10x faster than Python array.array
• xxhash3 wrapper provides 5 GB/s content fingerprinting
• mmap file loading enables zero-copy parse source
• Py_MOD_GIL_NOT_USED ensures free-threading compatibility (enforced by tests/conftest.py GIL probe)

Trade-off: C extension adds build complexity and platform-specific risks. Mitigated by Python fallback pattern (try import _native, fall back to pure Python).

GPT-4.1 adversarial review finding #2: "C extension build/deploy fragility."

Mitigation: Python fallback ensures engine works without C extension. Target platform is Linux only (Incus containers). janus-swi pattern is proven in this exact project.

4. Performance Targets

Benchmark gate (Wave 0): Measure LibCST parse speed on real codebase before finalizing targets. If parallel parse does not achieve 3x speedup, adjust targets or investigate LibCST thread-safety limitations.

Critical insight: The codebase is 2,500 files / 780K LOC (30 MB on disk). LibCST expands this ~15-20x to ~500-600 MB in memory, resulting in ~3 GiB RSS with Python object overhead. Eager parse loads the full codebase in <120s (parallel, 12 cores) and keeps it in memory for immediate graph queries and multihop analysis.

5. File Manifest

5.1 Source Files

Total: ~5,500 LOC Python

5.2 Test Files

Total: 81 BDD scenarios + 15 plain pytest tests = 96 tests

5.3 Gherkin Feature Files

Total: 12 feature files, 81 scenarios

5.4 Prolog

5.5 C Extension

Total: ~700 LOC C

5.6 Contracts and Briefs

6. Wave Execution Plan

Wave -1: Contract Authoring (Claude, ~30 min)

Files:

• plans/contracts/spec-110-codemod-engine.mmd (Mermaid classDiagram)
• plans/contracts/spec-110-codemod-engine.contract.json (machine-readable metadata)
• src/orchestrata_ultimate/prolog/codemod_review.pl (Prolog semantic review predicates)

Deliverables:

• Complete class diagram with %% traces annotations, <<class>>/<<Protocol>>/<<dataclass>> stereotypes, composition relationships
• Contract JSON with classes[], reuse[], rejected[], wiring{}, test_plan[]
• Prolog predicates for pass safety, blast radius, import cycles, rename safety, string replacement safety

Wave 0: Scaffold (Haiku, ~15 min)

Agent: SCAFFOLD (Haiku)
Files:

• refactor/codemod/report.py (ChangeEntry, ChangeSet, Finding, WorkspaceStats, CommitReport, CodemodEvent)
• refactor/codemod/__init__.py (public surface exports)
• tests/refactor/codemod/conftest.py (shared fixtures + BDD step definitions)

Tasks:

1. Run uv add libcst xxhash to add dependencies
2. Run gen-skeleton on the Mermaid contract to generate typed skeletons
3. Split monolithic gen-skeleton output into per-module files
4. Write conftest.py with codemod_repo, fixture_package, and shared BDD steps
5. Gate 0: Verify every skeleton class imports and constructs

Commit: SPEC-110: scaffold — skeletons, types, conftest, libcst+xxhash deps

Wave 1: FOREST + SENTINEL (Qwen Max + Sonnet, ~20 min, parallel)

Agent 1: FOREST (Qwen Max)
Files:

• refactor/codemod/workspace.py (CodemodWorkspace: load, forest, run, commit)
• refactor/codemod/_csr_index.py (CSR dependency index)
• refactor/codemod/_cig.py (Code Intelligence Graph)
• refactor/codemod/_cig_builder.py (build CIG from CST forest)
• tests/refactor/codemod/test_workspace_load.py (7 BDD scenarios)
• tests/refactor/codemod/test_workspace_index.py (6 BDD scenarios)
• tests/refactor/codemod/test_code_intelligence_graph.py (10 BDD scenarios)
• tests/refactor/codemod/test_csr_index.py (6 plain pytest tests)

Brief: Fill # IMPLEMENT: leaves in workspace.py, _csr_index.py, _cig.py, _cig_builder.py. Key LibCST APIs: libcst.parse_module(source), module.code, walk module.body for Import/ImportFrom/ClassDef/FunctionDef. Design decisions: demand-driven parse, parallel parse via ThreadPoolExecutor, CSR adjacency arrays, BFS transitive closure.

Agent 2: SENTINEL (Sonnet)
Files:

• refactor/codemod/txn.py (transactional write-back)
• tests/refactor/codemod/test_transactional_writeback.py (6 BDD scenarios)

Brief: Fill # IMPLEMENT: leaves in txn.py. Key invariants (from SPEC-109 applier.py): path confinement, snapshot before write, batch fsync, post-write verify, rollback on failure, concurrent-edit guard (mtime + hash + O_NOFOLLOW + flock).

Integration: Write all files, run pytest tests/refactor/codemod/test_workspace_load.py tests/refactor/codemod/test_txn.py -p orchestrata_ultimate.core.threading.pytest_live_observer, fix issues, commit.

Commit: SPEC-110: forest + sentinel — workspace, CIG, CSR, txn

Wave 2: ARCHITECT + REVIEWER (Qwen Max + Sonnet, ~20 min, parallel)

Agent 1: ARCHITECT (Qwen Max)
Files:

• refactor/codemod/passes.py (TransformPass ABC + 5 built-in passes)
• refactor/codemod/analysis/*.py (7 analysis modules)
• tests/refactor/codemod/test_transform_passes.py (8 BDD scenarios)
• tests/refactor/codemod/test_analysis_passes.py (8 BDD scenarios)

Brief: Fill # IMPLEMENT: leaves in passes.py and analysis/*.py. Key LibCST transformer patterns: CSTTransformer with visit_SimpleString/leave_SimpleString for string replacement, m.Import/m.ImportFrom for import manipulation, EmptyLine nodes for comments. Per-file parallelism: parallelism == "per_file" dispatches apply_file(path, tree, ws) to ThreadPoolExecutor.

Agent 2: REVIEWER (Sonnet)
Files:

• refactor/codemod/review.py (ReviewPass ABC + 40 in-memory checks)
• refactor/codemod/observability/*.py (6 observability modules)
• tests/refactor/codemod/test_review_before_write.py (8 BDD scenarios)
• tests/refactor/codemod/test_in_memory_review.py (8 BDD scenarios)
• tests/refactor/codemod/test_observability.py (6 BDD scenarios)

Brief: Fill # IMPLEMENT: leaves in review.py and observability/*.py. Key patterns: CSTTransformer/CSTVisitor for checks, SyncObservable[CodemodEvent] for observer dispatch, log-and-continue policy for observer errors. 40 checks organized into 7 categories (complexity, style, quality, structure, safety, correctness, test isolation).

Integration: Write all files, run full codemod test suite, fix issues, commit.

Commit: SPEC-110: architect + reviewer — passes, analysis, review, observability

Wave 3: INTEGRATOR (Qwen Max, ~15 min)

Agent: INTEGRATOR (Qwen Max)
Files:

• scripts/codemod.py (CLI: load-bench, run, report, analyze)
• tests/refactor/codemod/test_cli.py (5 BDD scenarios)
• tests/refactor/codemod/test_spec109_interop.py (4 BDD scenarios)
• tests/refactor/codemod/test_benchmark_load.py (3 plain pytest tests)

Brief: Implement CLI with argparse, SPEC-109 interop (RenameSymbolPass consumes WorkspaceEditPlan), benchmark tests. Key tasks: convert LSP text edits to LibCST mutations via libcst.metadata.PositionProvider, verify identical results between EditApplier and RenameSymbolPass, measure parse time and RSS delta.

Integration: Run acceptance demo (python scripts/codemod.py run --pass replace-string --arg old=NEO4J --arg new=GRAPH), full test suite, commit.

Commit: SPEC-110: integrator — CLI, SPEC-109 interop, benchmark

Wave 4: PERSISTENCE (Qwen Max, ~15 min)

Agent: PERSISTENCE (Qwen Max)
Files:

• refactor/codemod/persistence/repository.py (CodemodGraphRepository Protocol)
• refactor/codemod/persistence/bolt_repository.py (BoltSyncCodemodRepository)
• tests/refactor/codemod/test_graph_persistence.py (5 BDD scenarios)
• src/orchestrata_ultimate/knowledge_graph/canonical_schema.py (add new labels and relationships)

Brief: Implement repository pattern with Protocol, BoltSyncCodemodRepository using SyncGraphRepository.unit_of_work() for transactional writes. Cypher MERGE patterns for CodemodRun, CodemodPass, CodemodFinding, CodeChange nodes. Extend canonical_schema.py with new labels (CodemodRun, CodemodPass, CodemodFinding, CodeChange) and relationships (HAS_CODEMOD_RUN, HAS_PASS, HAS_FINDING, ABOUT, PRODUCED_BY, BREAKING_CHANGE).

Integration: Run graph persistence tests against real graph DB, verify Cypher patterns, commit.

Commit: SPEC-110: persistence — repository, graph writer, ontology

Wave 5: C EXTENSION (Qwen Max, ~20 min)

Agent: C-EXT (Qwen Max)
Files:

• scripts/_codemod_fast/pyproject.toml (setuptools build config)
• scripts/_codemod_fast/setup.py (Extension declaration)
• scripts/_codemod_fast/codemod_fast/csr_index.c (CSR build + BFS in C)
• scripts/_codemod_fast/codemod_fast/content_hash.c (xxhash3 wrapper)
• scripts/_codemod_fast/codemod_fast/mmap_loader.c (mmap file loading)
• scripts/_codemod_fast/codemod_fast/module.c (PyModuleDef with Py_MOD_GIL_NOT_USED)
• tests/refactor/codemod/test_c_extension.py (6 plain pytest tests)

Brief: Create C extension sub-package following janus-swi vendored-fork pattern. Critical: module.c MUST declare Py_mod_gil = Py_MOD_GIL_NOT_USED or the entire process loses free-threading. Python fallback pattern: try import _native, fall back to pure Python. Wire in root pyproject.toml via [tool.uv.sources] and no-build-isolation-package.

Integration: Run uv sync --dev, verify import, run C extension parity tests (Python impl and C impl produce identical results), commit.

Commit: SPEC-110: c extension — _codemod_fast sub-package

Wave 6: QUALITY (Claude, ~15 min)

Tasks:

1. Run all 6 gates:

   .venv/bin/ruff check src tests scripts
   .venv/bin/black --check src/orchestrata_ultimate/refactor/codemod tests/refactor/codemod scripts/codemod.py
   PYTHONPATH=src .venv/bin/python scripts/serialize_codebase_ast.py standards
   PYTHONPATH=src .venv/bin/python scripts/serialize_codebase_ast.py check-deps --include-tests
   PYTHONPATH=src .venv/bin/python scripts/test-review.py tests/refactor/codemod/ --stdout
   PYTHONPATH=src .venv/bin/python scripts/pyright_ratchet.py --max 283
   

2. Coverage:

   PYTHONPATH=src .venv/bin/python -m pytest tests/refactor/codemod/ \
     --cov=orchestrata_ultimate.refactor.codemod --cov-report=term-missing \
     -p orchestrata_ultimate.core.threading.pytest_live_observer \
     -o addopts=""
   

   Target: ≥90% per file.

3. Skeleton-diff:

   PYTHONPATH=src .venv/bin/python scripts/serialize_codebase_ast.py skeleton-diff \
     <skeleton> <final> --leafmap <leafmap>
   

4. Generate TASK_BRIEF.md report.

5. Final commit on feat/codemod-engine.

Commit: SPEC-110: quality — gates, coverage, skeleton-diff, report

7. Adversarial Review Findings (GPT-4.1)

GPT-4.1 identified 20 findings (4 CRITICAL, 5 HIGH, 4 MEDIUM, 7 LOW). Triage:

CRITICAL Findings

HIGH Findings

MEDIUM/LOW Findings

Plan Amendments (Post-Review)

1. Wave 0 benchmark gate: Measure LibCST parse speed on real codebase before finalizing performance targets
2. txn.py: Add O_NOFOLLOW + fcntl.flock to concurrent-edit guard design
3. GraphWriterObserver: Add batching + buffer-overflow-drop semantics
4. spec.md §1: Add "repos >10K files" as explicit non-goal
5. spec.md §11: Add threat model section
6. test plan: Add Hypothesis property-based tests for CSR/CIG (deferred to Phase 2)
7. design doc §9: Add incremental codemod to deferred features

8. Graph Ontology Additions

8.1 New Labels

8.2 New Relationships

8.3 Cypher MERGE Patterns

// CodemodRun node + HAS_CODEMOD_RUN edge
MERGE (r:CodemodRun {id: $id})
SET r.started_at = datetime($started_at),
    r.completed_at = datetime($completed_at),
    r.status = $status,
    r.dry_run = $dry_run,
    r.pass_count = $pass_count,
    r.finding_count = $finding_count,
    r.file_count = $file_count,
    r.duration_ms = $duration_ms
WITH r
MATCH (p:Project {slug: $project})
MERGE (p)-[:HAS_CODEMOD_RUN]->(r)

// CodemodPass nodes + HAS_PASS edges (batched)
UNWIND $passes AS pass
MERGE (cp:CodemodPass {id: pass.id})
SET cp.pass_name = pass.pass_name,
    cp.pass_type = pass.pass_type,
    cp.file_count = pass.file_count,
    cp.duration_ms = pass.duration_ms
WITH cp, pass
MATCH (r:CodemodRun {id: pass.run_id})
MERGE (r)-[:HAS_PASS]->(cp)

// CodemodFinding nodes + HAS_FINDING + ABOUT edges (batched)
UNWIND $findings AS f
MERGE (cf:CodemodFinding {id: f.id})
SET cf.severity = f.severity,
    cf.rule = f.rule,
    cf.path = f.path,
    cf.line = f.line,
    cf.message = f.message
WITH cf, f
MATCH (r:CodemodRun {id: f.run_id})
MERGE (r)-[:HAS_FINDING]->(cf)
WITH cf, f
OPTIONAL MATCH (m:Module {id: f.module_id})
FOREACH (_ IN CASE WHEN m IS NOT NULL THEN [1] ELSE [] END |
    MERGE (cf)-[:ABOUT]->(m))

// CodeChange nodes + PRODUCED_BY + CHANGED_IN edges (batched)
UNWIND $changes AS c
MERGE (cc:CodeChange {id: c.id})
SET cc.pass_name = c.pass_name,
    cc.description = c.description,
    cc.diff_hash = c.diff_hash
WITH cc, c
MATCH (r:CodemodRun {id: c.run_id})
MERGE (cc)-[:PRODUCED_BY]->(r)
WITH cc, c
MATCH (entity {id: c.entity_id})
MERGE (entity)-[:CHANGED_IN]->(cc)

9. Deferred Features

The following features are explicitly deferred to Phase 2 or later:

10. Daemon Architecture (REQ-110-133 — REQ-110-140)

10.1 Problem: Cold Start Cost

The engine parses 2,500 files (120s, 3 GiB RSS) on every invocation. This is unacceptable for:

• Interactive use (IDE plugins, REPL sessions)
• Multiple sequential operations (query → transform → query again)
• CI/CD pipelines running multiple codemods

10.2 Solution: Long-Running Daemon

Architecture:

• Daemon process: Keeps workspace in memory (3 GiB RSS) between invocations
• IPC: Unix socket at .codemod_daemon/socket (fast, local-only, secure)
• Protocol: JSON-RPC 2.0 (simple, well-supported, language-agnostic)
• File watching: inotify to detect changes and trigger incremental reload
• Lifecycle: codemod daemon start|stop|status|restart subcommands

Performance:

• Daemon startup: 120s parse (one-time cost)
• Subsequent CLI invocations: <100ms (IPC round-trip)
• File change detection: <500ms (inotify event + incremental re-parse)

Concurrency:

• Single daemon per repo (enforced by lock file .codemod_daemon/lock)
• Multiple clients can connect simultaneously (read operations)
• Write operations serialized via mutex

Requirements mapping:

• REQ-110-133: Long-running daemon, keeps workspace in memory, parses once at startup (120s), serves via Unix socket IPC (<100ms)
• REQ-110-134: Unix socket at .codemod_daemon/socket, JSON-RPC 2.0, PID file, lock file
• REQ-110-135: Lifecycle via codemod daemon start|stop|status|restart; start forks, parses, creates socket, starts inotify; stop sends SIGTERM, waits 5s, force kills
• REQ-110-136: inotify file watching; incremental re-parse on modify/create/delete/move; updates CIG and CSR; <500ms
• REQ-110-137: Concurrent clients; parallel reads; serialized writes (mutex); exclusive reload lock
• REQ-110-138: JSON-RPC methods: query_dependencies, query_dependents, query_blast_radius, query_breaking_changes, query_cycles, query_topological_order, query_affected_tests, query_coupling_score, query_abstraction_level, query_centrality, query_impact_score, run_pass, commit, reload, status
• REQ-110-139: Python client library (CodemodClient), Unix socket connection, context manager protocol
• REQ-110-140: CLI auto-connects to daemon, --auto-start flag, falls back to library mode with warning

10.3 Daemon Lifecycle

Start:

codemod daemon start [--repo /path/to/repo]

• Fork to background
• Parse workspace (120s)
• Create Unix socket at .codemod_daemon/socket
• Write PID to .codemod_daemon/pid
• Start inotify watcher thread

Stop:

codemod daemon stop

• Send SIGTERM to daemon PID
• Wait for graceful shutdown (5s timeout)
• Force kill if necessary
• Remove socket and PID file

Status:

codemod daemon status

• Check if PID file exists and process is running
• Report uptime, memory usage, client count
• Report last reload time

Restart:

codemod daemon restart

• Stop + start

10.4 IPC Protocol (JSON-RPC 2.0)

Request format:

{
  "jsonrpc": "2.0",
  "method": "query_blast_radius",
  "params": {"node_id": "pkg.module.Class", "hops": 3},
  "id": 1
}

Response format:

{
  "jsonrpc": "2.0",
  "result": {
    "affected_nodes": ["pkg.module.Class", "pkg.other.Function"],
    "affected_files": ["pkg/module.py", "pkg/other.py"],
    "impact_score": 0.42
  },
  "id": 1
}

Error format:

{
  "jsonrpc": "2.0",
  "error": {
    "code": -32602,
    "message": "Invalid params: node_id not found"
  },
  "id": 1
}

Methods:

• query_dependencies(node_id) → list of node IDs
• query_dependents(node_id) → list of node IDs
• query_blast_radius(node_id, hops) → BlastRadius object
• query_breaking_changes(change) → list of BreakingChange objects
• query_cycles() → list of cycles
• query_topological_order() → list of node IDs
• query_affected_tests(function_ids) → list of test IDs
• query_coupling_score(node_id) → CouplingScore object
• query_abstraction_level(node_id) → float
• query_centrality(top_k) → list of (node_id, score) tuples
• query_impact_score(node_id) → float
• run_pass(pass_name, params) → ChangeSet object
• commit(changes, reviews, dry_run) → CommitReport object
• reload() → force workspace reload (bypass inotify)
• status() → daemon status (uptime, memory, clients)

10.5 File Watching (inotify)

Implementation:

import inotify.adapters

def watch_files(self, repo_root: Path) -> None:
    """Watch for file changes and trigger incremental reload."""
    i = inotify.adapters.InotifyTree(str(repo_root))
    
    for event in i.event_gen(yield_nones=False):
        (_, type_names, path, filename) = event
        
        if "IN_MODIFY" in type_names or "IN_CREATE" in type_names:
            # File modified or created: incremental re-parse
            self._reload_file(Path(path) / filename)
        
        elif "IN_DELETE" in type_names:
            # File deleted: remove from forest
            self._remove_file(Path(path) / filename)
        
        elif "IN_MOVED_FROM" in type_names:
            # File moved: remove old path
            self._remove_file(Path(path) / filename)
        
        elif "IN_MOVED_TO" in type_names:
            # File moved: add new path
            self._reload_file(Path(path) / filename)

Incremental reload:

• Re-parse only the changed file(s)
• Update CIG and CSR index for affected nodes
• Invalidate any cached query results
• Emit workspace_reloaded event to connected clients

10.6 Concurrency Model

Read operations (parallel):

• Multiple clients can query simultaneously
• No locks needed (workspace is immutable between reloads)
• Use threading.Lock for CIG/CSR access (read-write lock)

Write operations (serialized):

• run_pass() and commit() acquire mutex
• Only one write operation at a time
• Clients waiting for mutex receive "operation in progress" error

Reload operations (exclusive):

• reload() acquires mutex
• Blocks all read/write operations during reload
• Clients receive "workspace reloading" error (retry after 500ms)

10.7 Client Library

Python client:

from orchestrata_ultimate.refactor.codemod.client import CodemodClient

with CodemodClient.connect(Path(".")) as client:
    # Query operations (fast, <100ms)
    deps = client.query_dependencies("pkg.module.Class")
    blast = client.query_blast_radius("pkg.module.Class", hops=3)
    
    # Transform operations (slower, 1-10s)
    changes = client.run_pass("ReplaceStringLiteralPass", {"old": "foo", "new": "bar"})
    report = client.commit(changes, dry_run=True)

CLI client:

# Query operations
codemod query dependencies pkg.module.Class
codemod query blast-radius pkg.module.Class --hops 3

# Transform operations
codemod run --pass replace-string --arg old=foo --arg new=bar
codemod commit --dry-run

10.8 Implementation Plan

Wave 1 (SENTINEL): Daemon skeleton + IPC protocol

• daemon.py: Daemon process lifecycle (start/stop/status)
• server.py: Unix socket server + JSON-RPC dispatcher
• client.py: Python client library
• lock.py: Lock file management (prevent multiple daemons)

Wave 2 (ARCHITECT): File watching + incremental reload

• watcher.py: inotify file watcher
• reload.py: Incremental re-parse + CIG/CSR update
• Integration with CodemodWorkspace

Wave 3 (INTEGRATOR): CLI integration

• codemod daemon start|stop|status|restart subcommands
• Auto-connect to daemon (or start if not running)
• Graceful fallback to library mode (no daemon)

10.9 Testing

BDD scenarios:

• daemon_lifecycle.feature: "Daemon start — parses workspace, creates socket, writes PID"
• daemon_lifecycle.feature: "Daemon stop — graceful shutdown, removes socket and PID"
• daemon_lifecycle.feature: "Daemon status — reports uptime, memory, client count"
• ipc_protocol.feature: "JSON-RPC request — query_dependencies returns list of node IDs"
• ipc_protocol.feature: "JSON-RPC error — invalid params returns error object"
• file_watching.feature: "File modified — inotify triggers incremental reload"
• file_watching.feature: "File deleted — inotify removes file from forest"
• concurrency.feature: "Multiple clients — parallel read operations succeed"
• concurrency.feature: "Write operation — mutex serializes concurrent writes"

Plain pytest tests:

• test_daemon.py: Unit tests for daemon lifecycle, lock file management
• test_server.py: Unit tests for JSON-RPC dispatcher, request/response handling
• test_client.py: Unit tests for Python client library
• test_watcher.py: Unit tests for inotify file watcher
• test_reload.py: Unit tests for incremental re-parse, CIG/CSR update

10.10 Performance Targets (Updated)

11. Risk Register

12. Success Criteria

The implementation is complete when:

• [ ] All 140 requirements (REQ-110-001 through REQ-110-140) are implemented and traced
• [ ] All 14 acceptance tests (TST-110-001 through TST-110-014) pass
• [ ] All 81 BDD scenarios pass
• [ ] All 15 non-BDD tests pass
• [ ] Coverage ≥90% per file
• [ ] All gates pass (ruff, black, standards, check-deps, test-review, pyright_ratchet)
• [ ] Performance targets met (parse time, query latency, RSS delta)
• [ ] Graph ontology additions committed to canonical_schema.py
• [ ] C extension builds and passes parity tests
• [ ] Prolog semantic review integrates with codemod_review.pl
• [ ] Observer architecture emits all 14 event types
• [ ] CLI accepts all subcommands (load-bench, run, report, analyze)
• [ ] SPEC-109 interop verified (RenameSymbolPass consumes WorkspaceEditPlan)
• [ ] Transactional write-back passes all rollback and concurrent-edit guard tests
• [ ] 40-check in-memory review executes without subprocess calls
• [ ] Code Intelligence Graph supports all multihop queries in <1ms
• [ ] Daemon lifecycle (start/stop/status/restart) works correctly with PID and lock file management
• [ ] IPC protocol (Unix socket + JSON-RPC 2.0) serves queries in <100ms
• [ ] inotify file watching triggers incremental reload in <500ms
• [ ] Concurrent clients: parallel reads succeed, writes serialized via mutex
• [ ] Python client library (CodemodClient) connects via Unix socket, supports context manager
• [ ] CLI auto-connects to daemon or falls back to library mode with warning

13. Conclusion

SPEC-110 defines the world's most advanced Python codemod engine, exploiting Python 3.14.6 free-threaded to achieve 6x parallel parse speedup, O(1) graph queries, and 40-check in-memory review without subprocess overhead.

The 10-layer architecture (CST forest, CIG, CSR index, transform passes, review passes, transactional write-back, observer architecture, graph persistence, Prolog semantic review, C extension) provides a complete code intelligence substrate that happens to also transform code.

The BDD test strategy (81 Gherkin scenarios across 12 feature files) ensures living documentation and behavioral specification. The adversarial review process (GPT-4.1 + Fable) identified and mitigated 20 findings, strengthening the design.

The wave execution plan (7 waves, 6 agents, 3 models) enables parallel development with clear integration points. The builder briefs (BRIEF-W0 through BRIEF-W5) provide detailed instructions for each agent.

This is not a codemod engine. This is a code intelligence platform.

Related

• Plans
• Orchestrata Ultimate — project index
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