Milestone 4 baseline

Scope and method

This baseline records the adapter SDK, Python reference adapter, incremental equivalence, and recovery behavior completed in Milestone 4. It was captured on 2026-07-29 from clean executable candidate 95271dcf2e48045b9d3aed9b9ea09c7fc155692c.

The maintained command was:

.venv/bin/python tools/milestone4_benchmark.py \
  --mode full \
  --output benchmarks/milestone4-2026-07-29.json

The synthetic project contains 334 Python files. Each file contributes one module, one function, and one argument node, for 1,002 primary nodes. Imports form a deterministic chain. Durations use time.perf_counter_ns() and nearest-rank p95. Each ordinary result is serialized as compact sorted JSON for its response-size gate. Per-operation memory uses tracemalloc; cumulative process high-water uses RUSAGE_SELF.

Environment:

Linux 7.1.3-200.nobara.fc44.x86_64 with glibc 2.43.
CPython 3.14.6.
x86_64.
Three warm samples; cold, equivalence, and recovery operations run once.
Per-operation traced-memory ceiling: 268,435,456 bytes.
Process high-water ceiling: 536,870,912 bytes.
Response ceiling: 524,288 bytes.

The complete machine-readable result is benchmarks/milestone4-2026-07-29.json. Its SHA-256 is b6a871dde730a119fc0a138c47bd25f2c533ed3171a9a3d098075aef08173600. The stable evidence payload SHA-256 is 4a8db461a311b5df4abd5aa00063e9a347d8b9dba19b30e35684f561d5271549.

Results

Operation	Median	p95	Limit	Traced peak	Response
Cold incremental build	1,599.760 ms	1,599.760 ms	20,000 ms	68,573,540 B	14,580 B
Warm incremental build	1,244.427 ms	1,265.387 ms	20,000 ms	69,997,166 B	14,578 B
Complete/incremental equivalence	1,897.919 ms	1,897.919 ms	30,000 ms	64,305,919 B	230 B
Corrupt extraction-cache recovery	1,695.406 ms	1,695.406 ms	30,000 ms	69,776,923 B	14,580 B
Corrupt index recovery	1,707.879 ms	1,707.879 ms	30,000 ms	68,561,924 B	14,779 B

Process high-water was 78,798,848 bytes. The regression limits intentionally leave multiple times the measured headroom; they are tripwires, not performance promises.

Deterministic graph and Logic evidence

The candidate produced:

1,002 primary nodes with hash f7705dedf8dd388857a20d11f459dc74de797bcd12d3ed36e7f3aa75d67c328f.
1,001 primary edges with hash 00cc90998b6783afc8c9d1fd900409e5e3ba352868c4ba30e9bb2cbd59c52d35.
334 Logic projections containing 2,338 Logic nodes and 2,338 Logic edges, with hash c86a3ae74777c2cec3a82c83e6e5bcca0196772ccea63cb13340fa9141593b0c.
Complete assembly hash 2888182ab765fbffe3ba873c1613345640e8e6d89be74ddfca7452c0a5056345.
Source hash 30ef23aa41061de2d4a7c995fe109d7a41518d9ee5493d805dd256581b47dae2.

The independently loaded complete assembly and the incremental assembly matched exactly across project identity, revision, source, nodes, edges, and Logic.

Work and recovery gates

The warm build recorded all 334 sources as cache hits, zero reparsed sources, zero ast.parse calls, and zero extract_source calls. Corrupting the extraction cache forced all sources through extraction and reproduced the same graph and Logic hashes. Corrupting SQLite rebuilt the index entirely from cache hits with zero parsing or extraction and reproduced those hashes.

This zero-parser evidence applies to the Python benchmark. Focused JavaScript and TypeScript tests prove parser-free manifests. The C++ reference manifest uses Tree-sitter for bounded quoted-include discovery and does not make a zero-warm-parser claim.

Fresh-wheel and reference evidence

The offline adoption proof built and installed the base wheel without Tree-sitter packages, built and checked a real Python reference project, started the isolated reference MCP server, and performed bootstrap, search, and exact retrieval over its 21 read tools. Selecting C++ without its extra failed with optional_dependency_missing and docforge[cpp] remediation.

Focused fixtures produced:

Python: 14 nodes, 13 edges, 5 Logic projections.
JavaScript: 14 nodes, 14 edges, 5 Logic projections.
TypeScript: 13 nodes, 14 edges, 4 Logic projections.
C++: 17 nodes, 16 edges, 5 Logic projections.

These fixture counts verify implementations; they are not language-wide completeness claims.

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