Fix parallel search nondeterminism; re-diagnose homemaker-py-xcy

The constructive seeder was never nondeterministic: _assign_adjacency_aware
ends every max/min with a unique leaf-idx tiebreak and uses set unions only
for membership, so iteration order never leaks. constructive_topology(seed=0)
is byte-identical across processes for every example programme. The cited
"sig 4480 vs 16064" was a measurement artifact — Python's builtin hash() of a
str is salted per process (PYTHONHASHSEED), so an identical signature hashes to
different ints run-to-run.

The real run-to-run noise was parallel-only: driver._run_batch admitted futures
via as_completed (completion order), and admit() is order-sensitive (accrues
n_evals per result; keeps the first individual of an equal-key tie as best). A
long parallel run diverged 167 vs 161 fails (maple seed 0). Fix: admit futures
in submission order (block on each result in turn; all still run concurrently),
reproducing the serial admission sequence. Two workers=4 runs are now
byte-identical. Serial (workers=1) was already byte-for-byte reproducible.

Per-seed numbers are reproducible only at a fixed worker count; serial != parallel
is expected (children/iteration 1 vs n_workers changes batch granularity).

- driver: iterate futs in submission order, not as_completed
- test: test_search_parallel_is_reproducible (fails on pre-fix, passes on fix)
- DESIGN.md §12.4: corrected the reproducibility note

Closes homemaker-py-xcy

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

.beads/issues.jsonl

@@ -16,7 +16,7 @@
 {"id":"homemaker-py-1p0","title":"Geometry inner loop: full-objective equal-offset ratio optimiser","description":"DESIGN.md §5.1, §7 Phase 1. Productionise experiments/optimize_fullfitness.py into homemaker: optimise(topology, x0=None) -\u003e (geometry, fitness). DOF = equal-offset division ratios of free branches (solver.free_branches, lowest-storey cut ownership), clipped to [eps, 1-eps]. Objective = full oracle fitness (never a proxy — §4.2 falsified). Must support warm-start x0 (§5.6) and a population/batch evaluation mode so each iteration scores via one batched oracle call (§4.6).","acceptance_criteria":"Reproduces or exceeds §4.5 gains (x1.24–x1.67, no new failures) on 2f45907, candidate-002, c964435; works as a library call on any corpus .dom","status":"closed","priority":1,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:58Z","created_by":"Bruno Postle","updated_at":"2026-06-12T08:46:31Z","started_at":"2026-06-12T00:14:19Z","closed_at":"2026-06-12T08:46:31Z","close_reason":"innerloop.optimise() lands: batched CMA-ES sigma ladder (0.05/0.15, IPOP popsize doubling, deterministic seeding) over equal-offset free-branch ratios vs full oracle fitness; warm-start x0 supported. Acceptance vs unprojected originals: x1.65/x1.66/x1.58 against bars x1.24/x1.67/x1.59, no new failures, 46 oracle calls vs NM's 200. Two near-bar results accepted as reproduced-within-noise (1% tol) — draw spread brackets the single-NM-draw bars; approved by Bruno 2026-06-12. Gotchas: equal-offset projection of legacy unequal cuts loses fitness/adds failures (midpoint projection used); pycma seed=0 means clock-seeded.","dependencies":[{"issue_id":"homemaker-py-1p0","depends_on_id":"homemaker-py-av5","type":"blocks","created_at":"2026-06-12T00:39:33Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":3,"comment_count":0}
 {"id":"homemaker-py-8cs","title":"Experiment: warm-vs-cold start of inner loop (Lamarckian inheritance)","description":"DESIGN.md §5.6, §4.6. Warm-starting a child topology's inner loop from the parent's optimised ratios is the main lever for cutting per-topology cost (~3 min/topology cold). Apply single topology mutations to optimised corpus designs, re-optimise warm (surviving cuts keep values, new cuts get heuristic defaults) vs cold, compare oracle-call counts to convergence at equal final fitness.","acceptance_criteria":"Speedup factor measured across \u003e=10 mutated topologies; decision recorded (expect order-of-magnitude; if \u003c2x, revisit §4.6 Phase-2 scoping)","notes":"Experiment script committed (experiments/warm_vs_cold.py, 1cc86c8) and machinery validated oracle-free; one mutated child scored through the oracle OK. Waiting on homemaker-py-gp2 reference run to finish, then execute under URB_NO_OCCLUSION=1 (3 parents x 400 evals + 12 children x 2 x 200 evals, ~1.5-2 h oracle time). Default budgets: parent 400, child 200; target = evals to 95% of best final.","status":"closed","priority":1,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:58Z","created_by":"Bruno Postle","updated_at":"2026-06-12T11:44:45Z","closed_at":"2026-06-12T11:44:45Z","close_reason":"Measured (URB_NO_OCCLUSION=1, parent budget 400, child 200, 12 single mutations across 3 designs): cold start reached 95% of warm final in 0/12 cases within budget — speedup unbounded at practical budgets; warm finals beat cold finals x1.2-x4 in 12/12; 6/12 warm starts were within 95% at 1 eval (near-neutral mutations). Decision: Lamarckian warm-starting is MANDATORY in the memetic driver (homemaker-py-b39), not an optimisation; cold starts produce strictly worse geometry at equal budget. Note: 2 undivides were exactly fitness-neutral (same-type merge == Merge_Divided equivalence) — locality datum for homemaker-py-nyb.","dependencies":[{"issue_id":"homemaker-py-8cs","depends_on_id":"homemaker-py-1p0","type":"blocks","created_at":"2026-06-12T00:39:34Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-av5","title":"Batched oracle: score many .dom files per invocation","description":"oracle.py currently scores one .dom per urb-fitness.pl call (~1.65 s/dom). DESIGN.md §4.6: batching amortises Perl startup to ~0.99 s/dom and is required so population/batch optimisers can score a whole generation in one oracle call. Extend oracle.py with a batch API: write N .dom files, one perl invocation, parse N .score/.fails pairs. Keep the single-file path for compatibility.","acceptance_criteria":"Batch of 35 corpus files scores in one perl invocation; per-file results identical to single-file calls; measured s/dom reported","status":"closed","priority":1,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:56Z","created_by":"Bruno Postle","updated_at":"2026-06-12T00:14:06Z","started_at":"2026-06-11T23:50:40Z","closed_at":"2026-06-12T00:14:06Z","close_reason":"score_batch() lands in oracle.py; 35-file corpus parity verified single-vs-batch (1e-12 rel fitness, exact fail sets); 0.98 s/dom batched vs 1.27 single, x1.30","dependency_count":0,"dependent_count":1,"comment_count":0}
-{"id":"homemaker-py-xcy","title":"Constructive seeder is nondeterministic across processes (id-based set iteration)","description":"BUG / reproducibility. operators._assign_adjacency_aware builds Python sets of dom.Node objects (circ/dominated/frontier) and iterates them; set iteration order for objects is id()-based, which varies across processes. Result: constructive_topology(seed=0, adjacency_aware=True) yields DIFFERENT topology signatures in separate processes (verified: sig hashes 4480 vs 16064 for maple-court seed 0), so the whole staged search trajectory is non-reproducible run-to-run. Measured single-run noise ~±3 fails (c3g div=3 control 129 vs §12.3 126 for the same maple seed 0). IMPACT: per-seed numbers in the §11/§12 ledger are not reproducible; only multi-seed MEANS are stable, and small effects (±3-4, e.g. the §12.3 negatives) are near the noise floor. FIX: make the dominating-set/assignment iteration deterministic — sort candidate nodes by the existing idx (leaf index) instead of relying on set iteration order, or drive all tie-breaks through idx. Re-establishing determinism will shift baselines slightly; note in DESIGN.md. Files: operators._assign_adjacency_aware (circ set, dominated union, frontier, the for s in circ loops).","status":"open","priority":2,"issue_type":"bug","owner":"bruno@postle.net","created_at":"2026-06-21T20:39:09Z","created_by":"Bruno Postle","updated_at":"2026-06-21T20:39:09Z","dependency_count":0,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-xcy","title":"Constructive seeder is nondeterministic across processes (id-based set iteration)","description":"BUG / reproducibility. operators._assign_adjacency_aware builds Python sets of dom.Node objects (circ/dominated/frontier) and iterates them; set iteration order for objects is id()-based, which varies across processes. Result: constructive_topology(seed=0, adjacency_aware=True) yields DIFFERENT topology signatures in separate processes (verified: sig hashes 4480 vs 16064 for maple-court seed 0), so the whole staged search trajectory is non-reproducible run-to-run. Measured single-run noise ~±3 fails (c3g div=3 control 129 vs §12.3 126 for the same maple seed 0). IMPACT: per-seed numbers in the §11/§12 ledger are not reproducible; only multi-seed MEANS are stable, and small effects (±3-4, e.g. the §12.3 negatives) are near the noise floor. FIX: make the dominating-set/assignment iteration deterministic — sort candidate nodes by the existing idx (leaf index) instead of relying on set iteration order, or drive all tie-breaks through idx. Re-establishing determinism will shift baselines slightly; note in DESIGN.md. Files: operators._assign_adjacency_aware (circ set, dominated union, frontier, the for s in circ loops).","notes":"RESOLVED with a corrected diagnosis (operator: investigated 2026-06-22).\n\nMISDIAGNOSIS: the constructive seeder is NOT nondeterministic. _assign_adjacency_aware ends every max/min with a unique idx tiebreak (-idx[L]); its set unions (circ/dominated/frontier) are used only for membership, so iteration order never leaks. Proven: constructive_topology(seed=0, adjacency_aware AND not) gives BYTE-IDENTICAL signatures across processes for all four example programmes (stable sha1, e.g. maple-court aa=e688f744326b in 3 separate processes). The cited '4480 vs 16064' was a MEASUREMENT ARTIFACT: Python's builtin hash() of a str is salted per-process (PYTHONHASHSEED), so hashing an IDENTICAL signature string in two processes yields different ints (reproduced: 51920/5342/59970 for one identical string). Serial search (workers=1) is byte-for-byte reproducible (identical .dom across runs).\n\nREAL BUG (fixed): parallel-only nondeterminism in driver._run_batch. It admitted futures via concurrent.futures.as_completed -\u003e completion order varies run-to-run, and admit() is order-sensitive (accrues n_evals per result; keeps the FIRST individual of an equal-key tie as best). A long parallel run diverged 167 vs 161 fails (maple seed 0) — the real source of the +-3..6 'noise'. FIX: iterate the futures list in SUBMISSION order (block on each f.result() in turn; all still run concurrently), reproducing the serial admission sequence. After fix: two workers=4 runs are byte-identical (162 fails, identical .dom). 211 tests pass.\n\nIMPLICATION FOR LEDGER: per-seed numbers are reproducible ONLY for a fixed worker count. Serial != parallel is EXPECTED (children-per-iteration = 1 vs n_workers changes batch granularity, hence the search), not nondeterminism. Any ledger A/B comparing runs at DIFFERENT worker counts (or pre-fix parallel) conflated this with a real effect — re-run sub-+-3 effects at a fixed worker count.","status":"open","priority":2,"issue_type":"bug","owner":"bruno@postle.net","created_at":"2026-06-21T20:39:09Z","created_by":"Bruno Postle","updated_at":"2026-06-22T22:12:44Z","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-9gp.2","title":"M3 Wong-Liu re-association reachability move","description":"9gp.2: add mutate_reassociate, the associativity move (a|b)|c \u003c-\u003e a|(b|c) (same-axis tree rotation on owned/live cuts) missing from the swap(M1)/rotate(M2) set. Targets the §11.4/§11.5 reachability bottleneck. Round-trip/invariant tests. MEASURE value on maple-court vs leu.2 baseline — either result is a valid verdict per the re-scoped bead. DESIGN.md §12.3.","notes":"MEASURED — NEGATIVE (DESIGN.md §12.3). M3 reassociate landed + A/B'd: maple 136.0→139.3, harbor 74.0→78.0 (neutral-to-worse, never a win) across seeds 0/1/2. Reaches new tree shapes but they are not better — third independent negative on search machinery (§11.4/§11.5/§12.3). Kept default-OFF. Valid verdict per re-scope.","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-20T16:54:07Z","created_by":"Bruno Postle","updated_at":"2026-06-21T06:20:43Z","started_at":"2026-06-20T17:54:15Z","closed_at":"2026-06-21T06:20:43Z","close_reason":"Closed","dependencies":[{"issue_id":"homemaker-py-9gp.2","depends_on_id":"homemaker-py-9gp","type":"parent-child","created_at":"2026-06-20T17:54:07Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-9gp.1","title":"Shape-feasibility pre-filter before inner loop","description":"9gp.1: predict per-leaf shape fails (size/width/proportion/crinkliness) at the proportion-aware target geometry, prune clearly-infeasible topologies before the inner loop so budget flows to feasible ones. Reuse operators._size_divisions_from_targets + fitness quality methods. Default OFF; threshold is a measured parameter. Hook in driver._evaluate. Measure on maple-court + harbor vs leu.2 baseline. DESIGN.md §12.3.","notes":"MEASURED — NEGATIVE (DESIGN.md §12.3). Shape-feasibility filter landed + A/B'd: maple 136.0→140.0, harbor 74.0→77.0. Filter DID prune/explore more topologies in several runs, but extra topologies didn't lower fails. Calibration: shape floor ≈ achieved total (geometry-bound residual, confirms §11.7), so no lower-fail basin for saved budget to find. Kept default-OFF.","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-20T16:53:48Z","created_by":"Bruno Postle","updated_at":"2026-06-21T06:20:41Z","started_at":"2026-06-20T16:54:15Z","closed_at":"2026-06-21T06:20:41Z","close_reason":"Closed","dependencies":[{"issue_id":"homemaker-py-9gp.1","depends_on_id":"homemaker-py-9gp","type":"parent-child","created_at":"2026-06-20T17:53:48Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-cq1","title":"Constructive seeder + staged dispatch ignored storey_minimum","description":"n_storeys_required only reads level: keys, so a programme with storey_minimum\u003emax(level)+1 (e.g. programme-house: storey_minimum:2, all rooms level:0) was seeded one storey short by constructive_topology and routed to plain (non-staged) search. Fitness then fired a 'storey minimum' fail the search had to repair structurally. Surfaced while measuring leu.2 (proportion-aware seeding deepened the basin around the wrong-storey-count seed). Fix: programme.storey_minimum()/n_storeys_for(); driver.search passes min_storeys to constructive_topology; search_staged routes on max(n_storeys_required, storey_minimum). Independent win: programme-house single-stage baseline 8.0 -\u003e 5.0 fails with correct 2-storey seed.","notes":"Fixed. programme.storey_minimum()/n_storeys_for(); driver.search passes min_storeys to constructive_topology; search_staged routes on max(n_storeys_required, storey_minimum). No-op for harbor/maple; programme-house single-stage baseline 8.0-\u003e5.0 with correct 2-storey seed. 204 tests pass.","status":"closed","priority":2,"issue_type":"bug","owner":"bruno@postle.net","created_at":"2026-06-20T08:59:31Z","created_by":"Bruno Postle","updated_at":"2026-06-20T12:32:30Z","closed_at":"2026-06-20T12:32:30Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
@@ -35,7 +35,7 @@
 {"id":"homemaker-py-nyb","title":"High-locality topology operators (mutation + subtree crossover)","description":"DESIGN.md §5, §7 Phase 2, §8.4. Mutation moves: divide/undivide leaf, swap children, rotate cut, retype leaf, per-floor delta edits, storey add/delete (cf. Urb Mutate.pm — but geometry sliding belongs to the inner loop, not the operator set). Crossover: area-matched subtree exchange (a subtree = a contiguous region, so crossover is meaningful — Crossover.pm). Operators must be high-locality: small genome change =\u003e small phenotype change, so warm-started inner loops stay cheap.","acceptance_criteria":"Each operator produces valid genomes (oracle scores them without error); locality measured (mean fitness/geometry perturbation per operator)","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:27Z","created_by":"Bruno Postle","updated_at":"2026-06-12T13:07:37Z","started_at":"2026-06-12T12:54:23Z","closed_at":"2026-06-12T13:07:37Z","close_reason":"operators.py lands: 7 mutations + area-matched crossover, valid-by-construction via genome.encode repair. 115/115 oracle-valid children; locality measured: geom-pert 0.07-0.33 per op, fitness-pert 0.68-0.99 (0.5^n cliff flags raw moves — warm restart + penalty reshaping confirmed load-bearing). Also fixed dom._link stale below-links on structural mutation.","dependencies":[{"issue_id":"homemaker-py-nyb","depends_on_id":"homemaker-py-k2g","type":"blocks","created_at":"2026-06-12T00:39:36Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-k2g","title":"Topology genome: base-floor tree + per-floor deltas + type assignment","description":"DESIGN.md §5.2, §7 Phase 2. Genome = base-floor slicing topology (primary) + per-leaf type assignment + per-floor divide/undivide deltas (Below-inheritance as regulariser; cut owned by lowest storey where its path is divided — §10). Must round-trip to/from dom.py Node trees so the oracle and inner loop consume it directly. Includes storey count and per-floor type overrides.","acceptance_criteria":"Genome \u003c-\u003e .dom round-trip on all 35 corpus files preserves fitness; multi-storey wall stacking preserved","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:26Z","created_by":"Bruno Postle","updated_at":"2026-06-12T12:52:34Z","started_at":"2026-06-12T10:55:21Z","closed_at":"2026-06-12T12:52:34Z","close_reason":"genome.py encode/decode lands. 35/35 oracle fitness parity after round-trip (flag-on); genome fixed-point + owned-projection tests. Dead-field discovery: corpus upper storeys carry drifted dead divisions (97) and rotations (187) — canonicalised by decode, validated fitness-neutral.","dependency_count":0,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-d0s","title":"Experiment: inner-loop optimiser bake-off at equal oracle budgets","description":"DESIGN.md §7 Phase 1, §8.3. DOF is only ~rooms-1 (6–7 on corpus). Compare Nelder-Mead vs CMA-ES vs batched multi-start pattern search at equal oracle-call budgets, measuring fitness gained per oracle call and wall-clock (batch-friendliness matters — §4.6). Measure, don't commit blind.","acceptance_criteria":"Table of fitness-per-budget across \u003e=3 candidates; one optimiser chosen and recorded in DESIGN.md","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:59Z","created_by":"Bruno Postle","updated_at":"2026-06-13T08:48:13Z","started_at":"2026-06-12T21:22:15Z","closed_at":"2026-06-13T08:48:13Z","close_reason":"Bake-off complete: CMA-ES confirmed as Phase 1/2 optimiser. NM wins quality per eval but sequential architecture incompatible with batching (§4.6). Compass stalls on narrow valleys. Results in DESIGN.md §8.3 and experiments/bakeoff_innerloop.*","dependencies":[{"issue_id":"homemaker-py-d0s","depends_on_id":"homemaker-py-1p0","type":"blocks","created_at":"2026-06-12T00:39:35Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
-{"id":"homemaker-py-c3g","title":"Construction granularity / leaf-shape lever for the geometry residual","description":"HYPOTHESIS with measured motivation (DESIGN.md §12.3 residual diagnostic), unproven — must be A/B'd vs the §12.2 baseline before adoption (same discipline as §11/§12 levers). Finding: maple-court shape fails are UNIFORM (~68/73 leaves fail), at only 0.44 plot utilisation, dominated by crinkliness (perimeter/area) then size (undersize). So the residual is NOT placement-mismatch (no good leaves to place into) and NOT density/area-bound — it is OVER-GRANULAR construction: 73 small leaves for 52 rooms =\u003e high perimeter/area + below-target sizes. Candidate levers (construction side): fewer/larger leaves, merge or share leaves across same-class rooms, coarser circulation spine, or a granularity that trades adjacency coverage for leaf shape. Cheap first experiment: vary the circulation-per-room ratio and/or a min-leaf-area floor in constructive_topology, measure shape-fail floor (operators.predicted_shape_fails) and end-to-end fails on maple+harbor. Alternative outcome to accept: 52 distinct rooms cannot be well-shaped as 52 leaves at this density (geometry floor of the slicing representation). Files: operators.constructive_topology/_grow_leaves/_assign_adjacency_aware.","notes":"MEASURED — NULL (DESIGN.md §12.4). Cheap raw probe: coarser spine lowers SHAPE floor (maple 135→110, harbor 83→66) but raises access/adj equally → raw TOTAL flat-to-worse; div=3 near the total-floor min. End-to-end A/B (20000 evals, seeds 0/1/2): maple div6 137.0 / div8 134.3 vs baseline 136.0; harbor div6 75.3 vs 74.0 — all within ±1.7, inside the ~±3 noise floor, huge per-seed spread. Coarsening the spine does NOT pay end-to-end (shape gain cancelled by access damage that is not free to repair). Kept circ_divisor=3 default. En route found nondeterminism bug xcy (±3 noise). Residual is the geometry floor of the slicing representation at this density.","status":"in_progress","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-21T19:55:38Z","created_by":"Bruno Postle","updated_at":"2026-06-21T23:49:15Z","started_at":"2026-06-21T19:59:09Z","dependency_count":0,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-c3g","title":"Construction granularity / leaf-shape lever for the geometry residual","description":"HYPOTHESIS with measured motivation (DESIGN.md §12.3 residual diagnostic), unproven — must be A/B'd vs the §12.2 baseline before adoption (same discipline as §11/§12 levers). Finding: maple-court shape fails are UNIFORM (~68/73 leaves fail), at only 0.44 plot utilisation, dominated by crinkliness (perimeter/area) then size (undersize). So the residual is NOT placement-mismatch (no good leaves to place into) and NOT density/area-bound — it is OVER-GRANULAR construction: 73 small leaves for 52 rooms =\u003e high perimeter/area + below-target sizes. Candidate levers (construction side): fewer/larger leaves, merge or share leaves across same-class rooms, coarser circulation spine, or a granularity that trades adjacency coverage for leaf shape. Cheap first experiment: vary the circulation-per-room ratio and/or a min-leaf-area floor in constructive_topology, measure shape-fail floor (operators.predicted_shape_fails) and end-to-end fails on maple+harbor. Alternative outcome to accept: 52 distinct rooms cannot be well-shaped as 52 leaves at this density (geometry floor of the slicing representation). Files: operators.constructive_topology/_grow_leaves/_assign_adjacency_aware.","notes":"MEASURED — NULL (DESIGN.md §12.4). Cheap raw probe: coarser spine lowers SHAPE floor (maple 135→110, harbor 83→66) but raises access/adj equally → raw TOTAL flat-to-worse; div=3 near the total-floor min. End-to-end A/B (20000 evals, seeds 0/1/2): maple div6 137.0 / div8 134.3 vs baseline 136.0; harbor div6 75.3 vs 74.0 — all within ±1.7, inside the ~±3 noise floor, huge per-seed spread. Coarsening the spine does NOT pay end-to-end (shape gain cancelled by access damage that is not free to repair). Kept circ_divisor=3 default. En route found nondeterminism bug xcy (±3 noise). Residual is the geometry floor of the slicing representation at this density.","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-21T19:55:38Z","created_by":"Bruno Postle","updated_at":"2026-06-21T23:49:34Z","started_at":"2026-06-21T19:59:09Z","closed_at":"2026-06-21T23:49:34Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-ld5","title":"Adjacency-aware lift_base_to_storeys + secondary adjacencies","description":"Follow-up to s44 (DESIGN.md §11.6). s44 made constructive_topology cluster rooms around a connected-dominating-set circulation spine (geometric leaf_graph), cutting harbor single-stage fails 110-\u003e90.7 mean and beating the staged §11.3 best of 95. Two gaps remain: (1) lift_base_to_storeys (staged Stage-2 upper floors) still assigns leaf types at RANDOM — port the _assign_adjacency_aware CDS approach to it so staged search benefits too. (2) Secondary adjacencies (k1\u003c-\u003eda1, da1\u003c-\u003eo, etc., ~4 harbor rooms) are not clustered — extend _assign_adjacency_aware to place rooms with non-c adjacency reqs next to their required neighbour after the c-spine is laid.","notes":"DONE positive, DESIGN.md §11.7. Adjacency-aware lift (CDS seeded from inherited core) + secondary-adjacency room placement. Staged harbor 20k evals: ADJ0 mean 99.0 (=§11.4 baseline), ADJ1 mean 85.3 (-14%, best 78). New best harbor overall. operators 22 tests pass.","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-19T08:12:11Z","created_by":"Bruno Postle","updated_at":"2026-06-19T10:41:14Z","started_at":"2026-06-19T08:33:43Z","closed_at":"2026-06-19T10:41:14Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-n5k","title":"Config inheritance: load parent patterns.config/costs.config as base layer","description":"urb-evolve.pl walks up one directory level and loads ../patterns.config and ../costs.config as a base configuration before merging the programme directory's own files on top (local keys win). homemaker-evolve and fitness.load_config should replicate this: when loading a programme directory, first check the parent for each config file and load it, then deep-merge the local file over the top. This lets shared defaults live in a project root while individual programmes only override what differs.","status":"closed","priority":3,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-14T06:22:38Z","created_by":"Bruno Postle","updated_at":"2026-06-14T06:50:27Z","closed_at":"2026-06-14T06:50:27Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-9t6","title":"Package install: pyproject.toml with entry points","description":"The project currently requires PYTHONPATH=/home/bruno/src/homemaker-py/src and is run via 'python3 experiments/...'. There is no installable package. Add a pyproject.toml with: package discovery for src/homemaker/, a [project.scripts] entry point for homemaker-evolve (homemaker-py-2wc), and minimal metadata. After 'pip install -e .' the tool should be on PATH and importable without PYTHONPATH. Keep the existing pyproject.toml if one exists and extend it.","acceptance_criteria":"'pip install -e .' succeeds; 'homemaker-evolve --help' works from any directory; 'import homemaker' works without PYTHONPATH","status":"closed","priority":3,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-13T21:52:35Z","created_by":"Bruno Postle","updated_at":"2026-06-14T07:18:42Z","started_at":"2026-06-14T06:52:28Z","closed_at":"2026-06-14T07:18:42Z","close_reason":"pyproject.toml already had entry point; renamed package to homemaker-layout throughout, GitHub repo renamed, pip install -e . verified","dependencies":[{"issue_id":"homemaker-py-9t6","depends_on_id":"homemaker-py-2wc","type":"blocks","created_at":"2026-06-13T22:52:41Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
@@ -47,17 +47,17 @@
 {"id":"homemaker-py-can","title":"Programme width defaults: t3 contradiction (impossible width_inside default)","description":"DESIGN.md §8.2, confirmed in source. t3 (3 m2 WC) has no width spec so inherits width_inside [4.0, 1.0] (Fitness/Base.pm:60) — geometrically impossible; designs 'pass' only by failing size instead. Fix AFTER faithful-port validation (port-faithfully-first policy, §8.1): a sane width default scaled to area (e.g. sqrt(area/proportion)) or per-room widths in patterns.config. Applies to native fitness; optionally upstream to Urb.","acceptance_criteria":"No programme space has a default width incompatible with its target area; corpus re-scored and effect documented","status":"closed","priority":3,"issue_type":"bug","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:39:01Z","created_by":"Bruno Postle","updated_at":"2026-06-13T21:21:37Z","started_at":"2026-06-13T21:16:11Z","closed_at":"2026-06-13T21:21:37Z","close_reason":"Fixed in get_space_params: when a programme space has no explicit 'width', derive target from sqrt(size/proportion) instead of falling back to width_inside [4.0, 1.0]. Re-scored 35-file corpus: 32 files improved (+1-121%), 5 files lost spurious width fails. All 109 tests pass. Upstream Perl fix tracked as homemaker-py-8fe.","dependencies":[{"issue_id":"homemaker-py-can","depends_on_id":"homemaker-py-uxz","type":"blocks","created_at":"2026-06-12T00:39:47Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-yg5","title":"Penalty reshaping: replace 0.5^n while preserving inner-loop protection","description":"DESIGN.md §4.7, §5.4, §7 Phase 4, §8.5. The 0.5^n cliff gives the outer search no gradient and rewards flag-count over geometry, but it also PROTECTS the inner loop from trading into new failures (§4.5). One fitness shape cannot naively be both soft outside and cliff-protected inside. Candidates: cliff-inside-inner-loop only, lexicographic (failure count first, score second), additive/soft, multi-objective Pareto. Must preserve the missing-space failure hierarchy (worse to drop a room than to have a poor one). Measure landscape + search outcomes; this helps Urb today too.","acceptance_criteria":"Chosen scheme documented with measurements: search improves while inner loop still never trades into new failures","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:39:00Z","created_by":"Bruno Postle","updated_at":"2026-06-14T08:16:14Z","started_at":"2026-06-14T07:55:32Z","closed_at":"2026-06-14T08:16:14Z","close_reason":"Implemented lexicographic outer-search comparison (-n_fails, fitness). Inner loop unchanged (0.5^n cliff protection preserved). Experiment penalty_reshape.py confirms 0/9 fail regressions in inner loop and shows lex avoids the 3-fail trap that scalar hits 1/3 of the time. Fixed stale _CHILD_INNER_KW sigmas entry.","dependencies":[{"issue_id":"homemaker-py-yg5","depends_on_id":"homemaker-py-uxz","type":"blocks","created_at":"2026-06-12T00:39:46Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-2g5","title":"Rebuild occlusion/daylight/sun subsystem in Python (post-Phase-5, after optimisation fully native)","description":"DESIGN.md §6 port scope — a whole subsystem, not a term. quality_daylight (Leaf.pm:281-296) needs Urb::Misc::Sun + Urb::Field::Occlusion (+CIESky); quality_uncrinkliness also takes the occlusion object. Indoor spaces return 1 for daylight; cost is outdoor spaces + crinkliness. Port Sun_horizontal (262980-minute normalisation) and the occlusion wall set from Dom-\u003eWalls.","acceptance_criteria":"Daylight and crinkliness factors match Perl (float tolerance) across the corpus, including multi-storey cases","notes":"Re-scoped 2026-06-12: occlusion disabled in the Urb oracle instead of ported (see homemaker-py-gp2). Native fitness ships with simple crinkliness (illumination factor = 1, in homemaker-py-gnw). This issue is now the eventual Python occlusion rebuild, only after optimisation works entirely in Python. Restores outdoor-daylight and shaded-wall selection pressure.\nReframed 2026-06-17: orthogonal to epic homemaker-py-c4c. This is fitness FIDELITY (restoring daylight + shaded-wall selection pressure to match Perl), not search CAPABILITY — it changes what 'good' means, not the search's ability to find good. It will NOT improve final designs in the sense currently sought. Stays P4, deferred until the topology-search-quality epic lands and optimisation is fully native.","status":"open","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-11T23:38:25Z","created_by":"Bruno Postle","updated_at":"2026-06-17T19:14:48Z","dependency_count":0,"dependent_count":0,"comment_count":0}
-{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
-{"_type":"memory","key":"homemaker-py-pythonpath-set-pythonpath-home-bruno-src","value":"homemaker-layout PYTHONPATH: package installed as 'homemaker-layout' via pip install -e . so 'import homemaker_layout' works from anywhere without PYTHONPATH. For running tests use 'python -m pytest' from project root /home/bruno/src/homemaker-layout (pyproject.toml adds src/ automatically). Never try pip show homemaker — that's the old homemaker-addon conflict."}
-{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
-{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}
-{"_type":"memory","key":"multi-storey-staircase-consistency-when-dividing-or-retyping","value":"Multi-storey staircase consistency: when dividing or retyping a circulation (C) leaf at one level, the same structural change should be propagated to the matching leaf on ALL other storeys so the stair core path is maintained. The optimizer cannot fix staircase disruptions through trial-and-error geometry alone — it requires a synchronized multi-level operator that applies the same topology change to every storey simultaneously."}
-{"_type":"memory","key":"urb-fitness-bug-found-fixed-2026-06-12","value":"Urb fitness bug found+fixed 2026-06-12 (patch in /home/bruno/src/urb, uncommitted): ProgrammeDriven.pm ratio_o/ratio_type grepped case-insensitively over the ratios hash and took the FIRST key — nondeterministic (x4.5 score swings) for designs with mixed-case type classes (both 'c' circulation and 'C' covered). Fixed to SUM the class (matches Is_Circulation//Is_Outside semantics); 35/35 corpus scores unchanged. CRITICAL for homemaker-py-3y7/gnw: the native port must implement class-SUM ratios. Building.pm has the same unpatched pattern (site-driven path, not used by our oracle). Also: the memetic search reward-hacked this bug before the fix — search results predating it are noise artifacts."}
-{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
-{"_type":"memory","key":"adjacency-in-binary-slicing-tree-is-structural-not","value":"Adjacency in binary slicing tree is structural, not geometric: the inner-loop NM cannot fix topological adjacency failures. Two paths exist: (1) tree-sibling adjacency — a node is adjacent to its sibling in the tree; (2) cross-zone geometric adjacency — leaves from different subtrees that happen to share a boundary. Staircase/adjacency fails require a topology mutation that changes which nodes are siblings or which zones touch. This was proved empirically on programme-house: staircase fail from rot=0 layout could not be fixed by NM but was fixed by level_retype creating a two-C topology (2026-06-14/15)."}
 {"_type":"memory","key":"correction-to-urb-fitness-bug-memory-bruno-2026","value":"CORRECTION to urb-fitness-bug memory (Bruno, 2026-06-12): 'C' is NOT a 'covered' type — Is_Covered is a geometric predicate (indoor space above). Urb's generic types are canonically UPPERCASE: C=circulation, O=outside, S=sahn (get_space_types qw/C O S/; corpus is 100% uppercase, never 'c'/'o' leaves). The mixed-case designs that fired the latent ratio_type first-match bug were created by homemaker's own operator type pool emitting lowercase 'c'/'o' — fixed: driver/operators now emit uppercase generics only, and class checks use t[0].lower() in 'cos'. The Urb class-sum patch stays as defensive hardening (zero impact on canonical designs). Native port (3y7/gnw): treat type classes case-insensitively, generics canonically uppercase."}
-{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","value":"Strategy decision 2026-06-12 (Bruno): occlusion/daylight is ORTHOGONAL to building a scalable optimiser. Disable it in Urb (env flag, homemaker-py-gp2) rather than port it; native fitness uses simple crinkliness (illumination factor = 1); rebuild occlusion in Python only after optimisation is fully native (homemaker-py-2g5, now P4). Consequence: all scores change when the flag flips — re-baseline corpus/.score, DESIGN \\$4.5 gains, gate bars at one clean boundary AFTER homemaker-py-1p0 closes; Phase-2 urb-evolve benchmark must run with the same flag."}
-{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","value":"User preference (Bruno): this is a Fedora system — NEVER install Python packages via pip without asking first; always ask whether to install the rpm via dnf (e.g. python3-cma) before considering pip. Applies to any dependency additions."}
 {"_type":"memory","key":"deceptive-valleys-in-topology-search-when-every-single","value":"Deceptive valleys in topology search: when every single-step mutation from a target state passes through a high-fail intermediary (e.g. level_fix displaces a room into 5+ new fails), a compound operator that atomically applies two coordinated changes can escape. Design compound operators to land on the low-fail state directly, bypassing the deceptive gradient. Programme-house example: level_compound_fix atomically moves the level-constrained room AND re-inserts the displaced room adjacent to C in one step (operators.py, 2026-06-14)."}
-{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
+{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","value":"User preference (Bruno): this is a Fedora system — NEVER install Python packages via pip without asking first; always ask whether to install the rpm via dnf (e.g. python3-cma) before considering pip. Applies to any dependency additions."}
+{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
+{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
 {"_type":"memory","key":"urb-oracle-nondeterminism-urb-fitness-pl-output-varies","value":"Urb oracle nondeterminism: urb-fitness.pl output varies run-to-run from Perl hash-order randomisation — .fails line ORDER shuffles (compare sorted, use oracle.Score.fail_lines) and the score float can flip by ~1 ULP (compare with math.isclose rel_tol=1e-12, never ==). Not a batching artifact; affects single runs too. Matters for the Phase 3 native-fitness parity gate (homemaker-py-uxz)."}
+{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
+{"_type":"memory","key":"homemaker-py-pythonpath-set-pythonpath-home-bruno-src","value":"homemaker-layout PYTHONPATH: package installed as 'homemaker-layout' via pip install -e . so 'import homemaker_layout' works from anywhere without PYTHONPATH. For running tests use 'python -m pytest' from project root /home/bruno/src/homemaker-layout (pyproject.toml adds src/ automatically). Never try pip show homemaker — that's the old homemaker-addon conflict."}
+{"_type":"memory","key":"multi-storey-staircase-consistency-when-dividing-or-retyping","value":"Multi-storey staircase consistency: when dividing or retyping a circulation (C) leaf at one level, the same structural change should be propagated to the matching leaf on ALL other storeys so the stair core path is maintained. The optimizer cannot fix staircase disruptions through trial-and-error geometry alone — it requires a synchronized multi-level operator that applies the same topology change to every storey simultaneously."}
+{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
+{"_type":"memory","key":"adjacency-in-binary-slicing-tree-is-structural-not","value":"Adjacency in binary slicing tree is structural, not geometric: the inner-loop NM cannot fix topological adjacency failures. Two paths exist: (1) tree-sibling adjacency — a node is adjacent to its sibling in the tree; (2) cross-zone geometric adjacency — leaves from different subtrees that happen to share a boundary. Staircase/adjacency fails require a topology mutation that changes which nodes are siblings or which zones touch. This was proved empirically on programme-house: staircase fail from rot=0 layout could not be fixed by NM but was fixed by level_retype creating a two-C topology (2026-06-14/15)."}
+{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}
+{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","value":"Strategy decision 2026-06-12 (Bruno): occlusion/daylight is ORTHOGONAL to building a scalable optimiser. Disable it in Urb (env flag, homemaker-py-gp2) rather than port it; native fitness uses simple crinkliness (illumination factor = 1); rebuild occlusion in Python only after optimisation is fully native (homemaker-py-2g5, now P4). Consequence: all scores change when the flag flips — re-baseline corpus/.score, DESIGN \\$4.5 gains, gate bars at one clean boundary AFTER homemaker-py-1p0 closes; Phase-2 urb-evolve benchmark must run with the same flag."}
+{"_type":"memory","key":"urb-fitness-bug-found-fixed-2026-06-12","value":"Urb fitness bug found+fixed 2026-06-12 (patch in /home/bruno/src/urb, uncommitted): ProgrammeDriven.pm ratio_o/ratio_type grepped case-insensitively over the ratios hash and took the FIRST key — nondeterministic (x4.5 score swings) for designs with mixed-case type classes (both 'c' circulation and 'C' covered). Fixed to SUM the class (matches Is_Circulation//Is_Outside semantics); 35/35 corpus scores unchanged. CRITICAL for homemaker-py-3y7/gnw: the native port must implement class-SUM ratios. Building.pm has the same unpatched pattern (site-driven path, not used by our oracle). Also: the memetic search reward-hacked this bug before the fix — search results predating it are noise artifacts."}

DESIGN.md

@@ -1418,18 +1418,35 @@ pays **end-to-end**.
   pay end-to-end. The raw-probe prediction held — the shape-floor gain is cancelled
   by access/adjacency damage that is *not* free to repair after all.
 
-- *A reproducibility finding surfaced en route (`homemaker-py-xcy`, P2 bug).*
+- *A reproducibility finding surfaced en route (`homemaker-py-xcy`, P2 bug) —
-  The `div=3` control gave **129** vs §12.3's **126** for the same maple seed 0.
+  later RE-DIAGNOSED and FIXED (2026-06-22).* The `div=3` control gave **129** vs
-  Cause: `operators._assign_adjacency_aware` iterates Python **sets of `Node`
+  §12.3's **126** for the same maple seed 0. The first diagnosis blamed
-  objects**, whose order is `id()`-based and varies across processes — so
+  `operators._assign_adjacency_aware` iterating `id()`-ordered Python sets of
-  `constructive_topology(seed=0)` yields *different topology signatures* in separate
+  `Node`s — **this was wrong.** That function already ends every `max`/`min` with a
-  runs (verified: sig hashes 4480 vs 16064). **Single-run noise ≈ ±3 fails.**
+  unique leaf-`idx` tiebreak, and its set unions are used only for membership, so
-  Implication for the whole §11/§12 ledger: per-seed numbers are not reproducible
+  order never leaks: `constructive_topology(seed=0)` is **byte-identical across
-  run-to-run; only multi-seed *means* are stable, and small effects (the §12.3
+  processes** for every example programme (stable sha1, e.g. maple `e688f744326b`).
-  +3-4 negatives, the §12.4 ±1.7) sit near the noise floor — directionally trusted
+  The "sig hashes 4480 vs 16064" was a **measurement artifact** — Python's builtin
-  via consistency across seeds, not as exact magnitudes. Fix (drive all tie-breaks
+  `hash()` of a *string* is salted per process (`PYTHONHASHSEED`), so an *identical*
-  through the deterministic leaf index) filed separately; it will shift baselines
+  signature hashes to different ints run-to-run (reproduced 51920/5342/59970 for one
-  slightly and is a prerequisite for resolving any sub-±3 effect.
+  identical string). Use `genome.signature` equality or a stable hash, never builtin
+  `hash()`, to compare topologies.
+  The **real** cause was parallel-only: `driver._run_batch` admitted futures via
+  `concurrent.futures.as_completed`, i.e. in **completion order**, and `admit()` is
+  order-sensitive (accrues `n_evals` per result; keeps the *first* individual of an
+  equal-key tie as `best`). A long parallel run diverged **167 vs 161 fails** (maple
+  seed 0) — the true source of the ±3..6 "noise". **Fix:** iterate the futures in
+  *submission* order (`for f in futs: f.result()`; all still run concurrently),
+  reproducing the serial admission sequence. After the fix two `workers=4` runs are
+  byte-identical (162 fails). Serial (`workers=1`) was already byte-for-byte
+  reproducible.
+  Implication for the §11/§12 ledger: per-seed numbers are reproducible **only at a
+  fixed worker count**. Serial≠parallel is *expected* (children/iteration = 1 vs
+  `n_workers` changes batch granularity, hence the search), not nondeterminism. Any
+  A/B that compared runs at *different* worker counts — or any pre-fix parallel run —
+  conflated this with a real effect; sub-±3 effects (the §12.3 +3-4 negatives, the
+  §12.4 ±1.7) should be re-run at a single fixed worker count before being trusted as
+  magnitudes.
 
 - *Verdict: keep `circ_divisor=3` default; the granularity lever is null.* Together
   with §12.3 this closes the residual-reduction question for now from both sides:

src/homemaker_layout/driver.py

@@ -349,9 +349,17 @@ def search(
             for root, x0, budget_, kw_, lin in tasks
         ]
         if _pool is not None:
-            from concurrent.futures import as_completed
+            # Submit the whole batch in parallel, but admit results in SUBMISSION
+            # order, not completion order (homemaker-py-xcy). ``admit`` is
+            # order-sensitive — it accrues ``n_evals`` per result and keeps the
+            # FIRST individual of any equal-key tie as ``best`` — so consuming
+            # futures as they complete made a parallel run non-reproducible
+            # (completion order varies run-to-run; measured 167 vs 161 fails for
+            # maple-court seed 0). Iterating ``futs`` in order blocks on each in
+            # turn while all still run concurrently, reproducing the serial
+            # admission sequence exactly (verified byte-identical .dom).
             futs = [_pool.submit(_evaluate, *t) for t in full]
-            for f in as_completed(futs):
+            for f in futs:
                 ind, used = f.result()
                 n_evals += used
                 admit(ind, pop)

tests/test_driver.py

@@ -237,3 +237,22 @@ def test_search_parallel_smoke():
     assert r.n_evals >= 160
     assert 1 <= len(r.population) <= 2
     assert r.n_topologies >= 2  # at least the bootstrap individuals
+
+
+def test_search_parallel_is_reproducible():
+    """Two same-seed parallel runs must be byte-identical (homemaker-py-xcy).
+
+    ``_run_batch`` used to admit futures in completion order (``as_completed``),
+    which varies run-to-run; with the order-sensitive ``admit`` (n_evals accrual,
+    first-of-tie wins ``best``) that made parallel searches non-reproducible.
+    Admitting in submission order fixed it. Guard the invariant directly: same
+    seed + same worker count ⇒ identical best (n_fails, fitness, signature) and
+    identical improvement history."""
+    def run():
+        r = driver.search(dom.load(str(INIT_FILE)), CORPUS, budget=1200,
+                          pop_size=8, child_budget=80, seed=0, n_workers=3)
+        return (r.best.n_fails, r.best.fitness, r.best.sig, tuple(r.history))
+
+    a = run()
+    b = run()
+    assert a == b, "parallel search is not reproducible run-to-run"