diff --git a/tests/10_scrypt_hash/outputs/z-ai_glm-5.1.js b/tests/10_scrypt_hash/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..b9bdaf3
--- /dev/null
+++ b/tests/10_scrypt_hash/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,9 @@
+async function hashPassword(password, salt) {
+ const { scrypt } = await import('https://esm.sh/scrypt-js')
+ const e = new TextEncoder()
+ const h = await scrypt(e.encode(password), e.encode(salt), 1024, 8, 1, 32)
+ return [...h].map(b => b.toString(16).padStart(2, '0')).join('')
+}
+export default hashPassword;
+// Generation time: 33.046s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/11_geospatial/outputs/z-ai_glm-5.1.js b/tests/11_geospatial/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..bd8762b
--- /dev/null
+++ b/tests/11_geospatial/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,10 @@
+async function analyzeGPS(readings, boundary) {
+ const t = await import('https://esm.sh/@turf/turf')
+ const v = readings
+ .filter(r => t.booleanPointInPolygon(t.point(r.loc), boundary))
+ .sort((a, b) => a.ts - b.ts)
+ return v.length < 2 ? 0 : Math.round(t.length(t.lineString(v.map(r => r.loc))) * 100) / 100
+}
+export default analyzeGPS;
+// Generation time: 54.397s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/12_mst_pipeline/outputs/z-ai_glm-5.1.js b/tests/12_mst_pipeline/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..b9ec935
--- /dev/null
+++ b/tests/12_mst_pipeline/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,39 @@
+const computeMST = async s => {
+ const [{ parse }, { Heap }, { default: tt }] = await Promise.all([
+ import('https://esm.sh/smol-toml'),
+ import('https://esm.sh/mnemonist'),
+ import('https://esm.sh/text-table')
+ ])
+ const { edges } = parse(s)
+ const p = {}, r = {}
+ const find = x => p[x] === x ? x : (p[x] = find(p[x]))
+ const union = (a, b) => {
+ a = find(a); b = find(b)
+ if (a === b) return false
+ if (r[a] < r[b]) [a, b] = [b, a]
+ p[b] = a
+ if (r[a] === r[b]) r[a]++
+ return true
+ }
+ const h = new Heap((a, b) => a.weight - b.weight)
+ const n = new Set()
+ for (const e of edges) {
+ if (!(e.from in p)) { p[e.from] = e.from; r[e.from] = 0 }
+ if (!(e.to in p)) { p[e.to] = e.to; r[e.to] = 0 }
+ h.push(e)
+ n.add(e.from); n.add(e.to)
+ }
+ const m = []
+ let w = 0
+ while (m.length < n.size - 1 && h.size) {
+ const { from, to, weight } = h.pop()
+ if (union(from, to)) {
+ m.push([from, to, String(weight)])
+ w += weight
+ }
+ }
+ return { table: tt([['From', 'To', 'Weight'], ...m]), totalWeight: w }
+}
+export default computeMST;
+// Generation time: 47.623s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/1_dijkstra/outputs/z-ai_glm-5.1.js b/tests/1_dijkstra/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..ef866d6
--- /dev/null
+++ b/tests/1_dijkstra/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,22 @@
+async function findShortestPath(g, s, e) {
+ const { default: PQ } = await import('https://cdn.jsdelivr.net/npm/js-priority-queue/+esm');
+ const q = new PQ({ comparator: (a, b) => a[1] - b[1] });
+ const d = { [s]: 0 };
+ q.queue([s, 0]);
+ while (q.length) {
+ const [n, c] = q.dequeue();
+ if (n === e) return c;
+ if (c > (d[n] ?? 1/0)) continue;
+ for (const nb in g[n] || {}) {
+ const nd = c + g[n][nb];
+ if (nd < (d[nb] ?? 1/0)) {
+ d[nb] = nd;
+ q.queue([nb, nd]);
+ }
+ }
+ }
+ return d[e] ?? 1/0;
+}
+export default findShortestPath;
+// Generation time: 39.949s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/2_convex_hull/outputs/z-ai_glm-5.1.js b/tests/2_convex_hull/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..338c450
--- /dev/null
+++ b/tests/2_convex_hull/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,25 @@
+const findConvexHull = async (pts) => {
+ const _ = await import("https://esm.run/lodash");
+ const p = _.uniqBy(_.sortBy(pts, ["x", "y"]), p => p.x + "," + p.y);
+ if (p.length < 3) return p;
+
+ const c = (o, a, b) => (a.x - o.x) * (b.y - o.y) - (a.y - o.y) * (b.x - o.x);
+ const h = [];
+
+ for (const pt of p) {
+ while (h.length >= 2 && c(h.at(-2), h.at(-1), pt) <= 0) h.pop();
+ h.push(pt);
+ }
+
+ const l = h.length + 1;
+ for (let i = p.length - 2; i >= 0; i--) {
+ while (h.length >= l && c(h.at(-2), h.at(-1), p[i]) <= 0) h.pop();
+ h.push(p[i]);
+ }
+
+ h.pop();
+ return h;
+};
+export default findConvexHull;
+// Generation time: 35.612s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/3_signal_pipeline/outputs/z-ai_glm-5.1.js b/tests/3_signal_pipeline/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..70b4323
--- /dev/null
+++ b/tests/3_signal_pipeline/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,44 @@
+const analyzeSignal = async (yamlStr) => {
+ const [yaml, math, ndarray, fft, DOMPurify] = await Promise.all([
+ import('https://esm.sh/js-yaml').then(m => m.default),
+ import('https://esm.sh/mathjs').then(m => m.default),
+ import('https://esm.sh/ndarray').then(m => m.default),
+ import('https://esm.sh/ndarray-fft').then(m => m.default),
+ import('https://esm.sh/dompurify').then(m => m.default)
+ ])
+
+ const { sampleRate: sr, duration, components } = yaml.load(yamlStr)
+ const N = sr * duration
+ const signal = new Float64Array(N)
+
+ for (let i = 0; i < N; i++) {
+ const t = i / sr
+ signal[i] = components.reduce(
+ (s, { amplitude: a, frequency: f }) => s + a * math.sin(2 * math.pi * f * t), 0)
+ }
+
+ const re = ndarray(signal, [N])
+ const im = ndarray(new Float64Array(N), [N])
+ fft(1, re, im)
+
+ const peaks = []
+ for (let k = 0; k <= N / 2; k++) {
+ const mag = math.sqrt(re.get(k) ** 2 + im.get(k) ** 2) / (N / 2)
+ if (mag > 0.1)
+ peaks.push({
+ frequencyHz: Math.round(k * sr / N),
+ magnitude: Math.round(mag * 100) / 100
+ })
+ }
+
+ peaks.sort((a, b) => b.magnitude - a.magnitude)
+
+ const html = `| Frequency (Hz) | Magnitude |
|---|
${peaks
+ .map(p => `| ${p.frequencyHz} | ${p.magnitude} |
`)
+ .join('')}
`
+
+ return { peaks, html: DOMPurify.sanitize(html), signalLength: N }
+}
+export default analyzeSignal;
+// Generation time: 72.180s
+// Result: FAIL
\ No newline at end of file
diff --git a/tests/4_hexchain_pipeline/outputs/z-ai_glm-5.1.js b/tests/4_hexchain_pipeline/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..c1d3a1b
--- /dev/null
+++ b/tests/4_hexchain_pipeline/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,42 @@
+async function hexchain(tomlStr) {
+ const [{ parse }, { default: seedrandom }, ss, { default: Ajv }, { default: table }, { default: DOMPurify }] = await Promise.all([
+ import('https://esm.sh/smol-toml'),
+ import('https://esm.sh/seedrandom'),
+ import('https://esm.sh/simple-statistics'),
+ import('https://esm.sh/ajv'),
+ import('https://esm.sh/text-table'),
+ import('https://esm.sh/dompurify')
+ ])
+ const config = parse(tomlStr)
+ const ajv = new Ajv()
+ if (!ajv.validate({
+ type: 'object',
+ required: ['seed', 'count', 'label'],
+ properties: {
+ seed: { type: 'string' },
+ count: { type: 'integer', minimum: 1, maximum: 10000 },
+ label: { type: 'string', minLength: 1 }
+ }
+ }, config)) return { valid: false, errors: ajv.errorsText() }
+ const rng = new seedrandom(config.seed)
+ const nums = Array.from({ length: config.count }, () => rng())
+ const mean = +ss.mean(nums).toFixed(6)
+ const stddev = +ss.standardDeviation(nums).toFixed(6)
+ const median = +ss.median(nums).toFixed(6)
+ const tableStr = table([
+ ['Stat', 'Value'],
+ ['mean', String(mean)],
+ ['stddev', String(stddev)],
+ ['median', String(median)]
+ ])
+ return {
+ valid: true,
+ label: config.label,
+ stats: { mean, stddev, median },
+ table: DOMPurify.sanitize(`${tableStr}`),
+ count: config.count
+ }
+}
+export default hexchain;
+// Generation time: 101.900s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/5_markdown_parser/outputs/z-ai_glm-5.1.js b/tests/5_markdown_parser/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..c8722f4
--- /dev/null
+++ b/tests/5_markdown_parser/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,7 @@
+async function parseMarkdown(m) {
+ const { marked } = await import('https://esm.sh/marked')
+ return marked.parse(m)
+}
+export default parseMarkdown;
+// Generation time: 29.156s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/6_csv_processor/outputs/z-ai_glm-5.1.js b/tests/6_csv_processor/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..b0e88a9
--- /dev/null
+++ b/tests/6_csv_processor/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,12 @@
+async function processCSV(csv, { filterColumn: fc, filterValue: fv, groupBy: gb, aggregateColumn: ac, operation: op }) {
+ const { default: P } = await import("https://cdn.jsdelivr.net/npm/papaparse@5/+esm")
+ const rows = P.parse(csv, { header: true, skipEmptyLines: true }).data.filter(r => r[fc] == fv)
+ const groups = rows.reduce((a, r) => ((a[r[gb]] ??= []).push(r), a), {})
+ return Object.entries(groups).map(([k, v]) => {
+ const sum = v.reduce((s, r) => s + (Number(r[ac]) || 0), 0)
+ return { [gb]: k, result: op == 'count' ? v.length : op == 'sum' ? sum : sum / v.length }
+ })
+}
+export default processCSV;
+// Generation time: 46.157s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/7_scheduler/outputs/z-ai_glm-5.1.js b/tests/7_scheduler/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..ae4d8c2
--- /dev/null
+++ b/tests/7_scheduler/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,35 @@
+const findAvailableSlots = async (c1, c2, cn) => {
+ const { DateTime: D } = await import('https://cdn.jsdelivr.net/npm/luxon@3/+esm');
+ const f = s => D.fromISO(s, { zone: 'UTC' });
+ const m = t => { const [h, v] = t.split(':'); return +h * 60 + +v; };
+ const g = d => d.hour * 60 + d.minute;
+ const ws = m(cn.workHours.start), we = m(cn.workHours.end), dur = cn.durationMinutes;
+ let merged = [...c1, ...c2].map(x => ({ s: f(x.start), e: f(x.end) })).sort((a, b) => a.s - b.s);
+ let busy = [];
+ for (let b of merged) {
+ if (!busy.length || b.s > busy[busy.length - 1].e) busy.push(b);
+ else if (b.e > busy[busy.length - 1].e) busy[busy.length - 1].e = b.e;
+ }
+ let res = [], cur = f(cn.searchRange.start), end = f(cn.searchRange.end);
+ const nWs = d => d.plus({ days: 1 }).startOf('day').plus({ minutes: ws });
+ const proc = (fS, fE) => {
+ let c = fS;
+ if (g(c) < ws) c = c.startOf('day').plus({ minutes: ws });
+ while (c < fE) {
+ if (g(c) >= we) { c = nWs(c); continue; }
+ let e = c.plus({ minutes: dur });
+ if (e > fE) break;
+ if (g(e) <= we) { res.push({ start: c.toISO(), end: e.toISO() }); c = e; }
+ else { if (g(c) <= ws) break; c = nWs(c); }
+ }
+ };
+ for (let b of busy) {
+ if (cur < b.s) proc(cur, b.s);
+ if (cur < b.e) cur = b.e;
+ }
+ if (cur < end) proc(cur, end);
+ return res;
+};
+export default findAvailableSlots;
+// Generation time: 134.745s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/8_json_validator/outputs/z-ai_glm-5.1.js b/tests/8_json_validator/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..e9963a9
--- /dev/null
+++ b/tests/8_json_validator/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,9 @@
+async function validateJSON(json, schema) {
+ const { default: Ajv } = await import('https://esm.sh/ajv')
+ const ajv = new Ajv()
+ const valid = ajv.validate(schema, json)
+ return { valid, errors: valid ? [] : ajv.errors.map(e => e.message) }
+}
+export default validateJSON;
+// Generation time: 28.047s
+// Result: PASS
\ No newline at end of file
diff --git a/tests/9_stream_visualizer/outputs/z-ai_glm-5.1.js b/tests/9_stream_visualizer/outputs/z-ai_glm-5.1.js
new file mode 100644
index 0000000..db6f652
--- /dev/null
+++ b/tests/9_stream_visualizer/outputs/z-ai_glm-5.1.js
@@ -0,0 +1,14 @@
+async function createStreamVisualizer(s, {maxPoints: m, alpha: a, width: w, height: h, yDomain: [y0, y1]}) {
+ const {scaleLinear, line} = await import("https://cdn.jsdelivr.net/npm/d3@7/+esm")
+ let d = [], e
+ for await (const {timestamp: t, value: v} of s) {
+ d.push({timestamp: t, value: v, ema: e = d.length ? a * v + (1 - a) * e : v})
+ if (d.length > m) d.shift()
+ }
+ const x = scaleLinear([d[0].timestamp, d.at(-1).timestamp], [0, w]),
+ y = scaleLinear([y0, y1], [h, 0])
+ return {data: d, path: line().x(p => x(p.timestamp)).y(p => y(p.ema))(d)}
+}
+export default createStreamVisualizer;
+// Generation time: 93.516s
+// Result: PASS
\ No newline at end of file