Ilia Denisov
c334a9d7b7
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First engine-first step of PWA offline mode (Phase A): the client-side move generator — the "robot brain" a local vs_ai game will run on-device — with no runtime wiring yet (Phase B). - dawg.ts: add the step-by-step cursor (root/final/next/arcs), a faithful port of dafsa traverse.go over the reader's existing bitstream. - generate.ts: the Appel-Jacobson generator (leftPart/extendRight + cross-sets + counts-rack + board transpose + moveKey ranking), reusing the cursor and validate.ts evaluate/connected. A cross-set LetterSet is a Uint8Array, so the 33-letter Russian alphabet (index 32) is exact under JS bit ops. - validate.ts: export connected for the generator's connectivity filter. - backend/cmd/movegen: dev tool building small sample dictionaries and emitting golden move-generation fixtures from the real Go solver (EN + RU). - tests: dawg.cursor.test.ts (enumeration bijection vs indexOf) and generate.parity.test.ts (7/7 vs the Go solver: empty board, mid-game, blank, single-word rule, Russian index-32 cross-set). The committed EN sample also unblocks the existing skipped dawg.parity.test.ts once wired with DICT_* in CI. Pure additive library code; no runtime behavior change.
69 lines
2.4 KiB
TypeScript
69 lines
2.4 KiB
TypeScript
import { describe, it, expect } from 'vitest';
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import { readFileSync } from 'node:fs';
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import { Dawg } from './dawg';
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// The step-by-step DAWG cursor (root/final/next/arcs) is the primitive the move
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// generator walks. These fast unit tests pin it against a small committed sample
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// dictionary (backend/cmd/movegen); the full parity vs the Go solver lands with
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// the generator's conformance fixtures.
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const bytes = new Uint8Array(readFileSync(new URL('./testdata/sample_en.dawg', import.meta.url)));
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const fixture = JSON.parse(
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readFileSync(new URL('./testdata/sample_en.words.json', import.meta.url), 'utf8'),
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) as { numAdded: number; words: string[]; indexes: number[][] };
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const key = (w: number[]): string => w.join(',');
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// enumerateWords walks the whole automaton depth-first, collecting the index path
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// at every accepting node — i.e. every stored word.
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function enumerateWords(d: Dawg): number[][] {
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const out: number[][] = [];
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const path: number[] = [];
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const visit = (node: number): void => {
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d.arcs(node, (label, dest, final) => {
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path.push(label);
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if (final) out.push(path.slice());
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visit(dest);
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path.pop();
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return true;
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});
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};
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if (d.final(d.root())) out.push([]);
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visit(d.root());
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return out;
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}
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describe('dawg cursor', () => {
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it('parses the sample fixture', () => {
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const d = new Dawg(bytes);
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expect(d.numAdded).toBe(fixture.numAdded);
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});
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it('root is not an accepting state (the sample has no empty word)', () => {
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const d = new Dawg(bytes);
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expect(d.final(d.root())).toBe(false);
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});
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it('enumerates exactly the stored words', () => {
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const d = new Dawg(bytes);
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const got = enumerateWords(d).map(key).sort();
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const want = fixture.indexes.map(key).sort();
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expect(got).toEqual(want);
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});
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it('next walks a stored word to an accepting node and rejects a non-edge', () => {
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const d = new Dawg(bytes);
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let node = d.root();
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for (const ch of [2, 0, 17, 4, 3]) {
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// "cared"
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node = d.next(node, ch);
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expect(node).toBeGreaterThanOrEqual(0);
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}
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expect(d.final(node)).toBe(true);
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// "care" (index [2,0,17,4]) is an internal accepting node on the way to "cared".
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const care = [2, 0, 17, 4].reduce((n, ch) => d.next(n, ch), d.root());
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expect(d.final(care)).toBe(true);
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// No stored word starts with 'z' (index 25).
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expect(d.next(d.root(), 25)).toBe(-1);
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});
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});
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