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gparse-eisner-dynamic-program

The groupant beside gparse/src/eisner.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

componentlabelwhere
ApproximantpartialApproximant
Astpartial../syntax.json
Costsymbolic source derivedInvariant
DescriptantpresentDescriptant
InvariantpartialInvariant
Testspartial bounded checksTests

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.

relationtypelabelwhere
Behavior complementbehavior complementpartial source derived modelBehavior complement
Reverse reconstructionreverse reconstructionpartial source derived modelReverse reconstruction
Chart basechart basepartial source derived modelChart base
Incomplete joinincomplete joinpartial source derived modelIncomplete join
Root constraintroot constraintpartial source derived modelRoot constraint
Tie ordertie orderpartial source derived modelTie order

Model text

Descriptant

Source-bound description

Span filling uses rounded f32 max-plus, stores earliest split for strict improvements, and selects one root. Exact-real maximum-tree interpretation requires exact arithmetic or candidate-order preservation.

Approximant

Forward approximant

Span filling uses rounded f32 max-plus, stores earliest split for strict improvements, and selects one root. Exact-real maximum-tree interpretation requires exact arithmetic or candidate-order preservation.

Domain: valid source-specific dimensions and resources stated in invariant; no automatic production substitution. Numerical observations are finite checks, not an end-to-end relative bound. Executable Rust surrogate: unsupported gap; existing exact tests are not surrogates. Future metric-specific caps may be 1/2/5/10%, never above 10%.

Invariant

Invariant and cost

Square scores with finite intermediates are needed for meaningful maximizing backpointers; f32 rounding can differ from real max-plus ordering.

Cost

O(n³) arithmetic, O(n²) charts/backpointers.

Allocation, finite arithmetic, platform dimensions and external failures are not universally certified.

Models

Typed model catalog

Behavior complement

A later equal candidate cannot replace earlier maximizing split/root.

Reverse reconstruction

A chosen split is compatible with candidate vectors whose rounded f32 comparisons select it; real-score inequality cones are valid only with order preservation. All -infinity candidates preserve fallback indices, which need not be first ascending.

Chart base

Complete singleton spans initialized0, others -infinity.

Incomplete join

Best C_left(s,r)+C_right(r+1,t) receives edge in either direction.

Root constraint

Only final root choice adds sc[0][r], ensuring one root child on admitted domain.

Tie order

For representable finite candidates, strict > and ascending r retain first maximum. If all candidates are -infinity, default a1=t can survive instead.

Tests

Checks and limits

Selected parent checks relevant to this fragment (not exhaustive): eisner::tests::best_tree_with_one_root; eisner::wave30::empty_singleton_and_first_root_tie; decoder_accepts_no_words

Selected commands run twice debug and twice release; exact receipts and source-to-test mapping retained in wave30 gparse external run directory. Tests do not certify allocation failure, all NaN/overflow inputs, trained-model accuracy or corpus timing. Compiled mutants cover selected boundaries; per-source coverage is recorded in the external map, not presumed.

History

2026-10-31 · descriptant

Epoch 2026-10-31

Prospective model was recorded before edits. Added tests use bounded synthetic fixtures; production algorithms unchanged. Coverage is partial, not proof. No trained corpus, live teacher or throughput experiment was executed.

Provenance

This page in Markdown → https://md.groupants.elamur.ai/free/en/mova/gparse/src/eisner.rs.groupant/dynamic-program.groupant/