Elamur Groupantshbo-lattice-selection
The groupant beside tools/hbo/src/lattice.rs in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.
Facts
Implementation material. A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.
Components
| component | label | where |
|---|---|---|
| approximant | partial | approximant |
| ast | partial | ../syntax.json |
| cost | symbolic source derived | invariant-and-cost |
| descriptant | present | descriptant |
| invariant | partial | invariant-and-cost |
| tests | executed bounded checks | tests |
Obernants
The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.
| id | type | label | where |
|---|---|---|---|
behavior_complement | behavior_complement | partial source derived model | behavior_complement |
reverse_reconstruction | reverse_reconstruction | partial source derived model | reverse_reconstruction |
base_overwrite | base_overwrite | partial source derived model | base_overwrite |
missing_score | missing_score | partial source derived model | missing_score |
gain_word_units | gain_word_units | partial source derived model | gain_word_units |
nonfinite_order | nonfinite_order | partial source derived model | nonfinite_order |
Model text
descriptant
Descriptant
2026-10-31, prospective epoch: inspected source before edits and predicted First pass builds base scores; second computes candidate gain and strict improvement choice.
Measured epoch: bounded supplied fixtures passed twice in debug and release; six behavioral mutants were rejected after compilation, each restored exactly. These observations support the scoped equations without extending them to corpus accuracy, semantic understanding or persistent learning. Production code bytes are unchanged; only isolated tests appended. No benchmark or percentage surrogate was introduced.
Retained caveats: Finite supplied-input checks only; no corpus, training, external annotator, GPU, throughput or semantic-understanding claim. Allocation exhaustion and malformed arbitrary model arithmetic are not exhaustively exercised. No useful numerical surrogate is implemented; future caps may only be 1/2/5/10% with a declared metric.
approximant
Forward relation
First pass builds base scores; second computes candidate gain and strict improvement choice.
Domain: All alternate sentence indices have a base; finite arithmetic for order semantics.
Source snapshot SHA-256: eeec78ace6a0dadfcff75205bc3718b223cf89d05fc8df94ea2884272f033fbf. This is a partial source-derived mathematical relation, not an executable surrogate. Tests exercise actual production helpers with synthetic inputs.
models
Typed model catalog
Subject: hbo-lattice-selection at SHA-256 eeec78ace6a0dadfcff75205bc3718b223cf89d05fc8df94ea2884272f033fbf. Domain and fixed state: All alternate sentence indices have a base; finite arithmetic for order semantics.. Observation: return values, stated mutations and failure order of this scope. Models are partial source-derived relations; finite tests can falsify them but do not prove general completeness. Behavior complement is a scoped exclusion claim in the admitted transition universe. Reverse reconstruction retains compatible antecedents, not a unique historical cause. Specialized entries hold this domain fixed and isolate their named observation. Oracle: named actual-code fixtures in tests.md; unexecuted effect boundaries remain static hypotheses.
behavior_complement
Zero gain cannot enter Choice; equal gain cannot displace prior label.
reverse_reconstruction
Fixed winner constrains score differences and all competing gains, leaving many absolute-score shifts possible.
base_overwrite
Last base for sentence overwrites earlier score/count.
missing_score
Missing base score Err, missing alternate score f64::MIN, missing base indexed panic.
gain_word_units
mu multiplies difference in flat word counts, not written token counts.
nonfinite_order
NaN gain fails >0; infinities require separate interpretation and are excluded from finite model.
tests
Bounded evidence
Primary actual-code fixture: lattice::wave32::supplied_readings_ties_missing_and_apply. Run using cargo test --offline --locked -p hbo --lib lattice::wave32::supplied_readings_ties_missing_and_apply -- --exact --test-threads=1; repeat with --release. The external wave32 Hbo receipt set contains all 14 named outcomes twice per profile, numeric exit statuses, six compiled behavioral source negatives and byte-exact restoration hashes, and two identical source syntax projections. Source-local primary tests include assertions and caught expected panics. Fragments share these source witnesses; no claim of one test per branch.
Finite supplied-input checks only; no corpus, training, external annotator, GPU, throughput or semantic-understanding claim. Allocation exhaustion and malformed arbitrary model arithmetic are not exhaustively exercised. No useful numerical surrogate is implemented; future caps may only be 1/2/5/10% with a declared metric.
invariant-and-cost
Invariant and cost
All alternate sentence indices have a base; finite arithmetic for order semantics.
Cost
For R parsed readings, S sentence keys and N token keys per sentence, choose takes O(T_R+B_R+R log S+R log N) time, with T_R=sum of reading token counts and B_R=comment bytes scanned/parsed across its constant passes. n_words scans token vectors rather than returning a cached count. Space is O(S+chosen tokens+retained label bytes).
Resources must permit allocations; cost variables are source bytes, units, words and table entries as explicitly stated. No measured speed or universal error claim.
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