perf(core): optimize sort/reverse permutation from O(n^2) to O(n)

.changeset/sort-permutation-on-optimization.md

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+---
+"@geajs/core": patch
+---
+
+### @geajs/core (patch)
+
+- **Sort/reverse permutation O(n) optimization**: Replace O(n^2) nested-loop permutation calculation with a Map-based O(n) index lookup, improving performance on large sorted arrays.

.gitignore

@@ -1,5 +1,7 @@
 node_modules
 .history
+.omc
+.serena
 .DS_Store
 dist
 dist-profile

packages/gea/benchmarks/sort-permutation.bench.ts

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+/**
+ * Benchmark: sort/reverse permutation O(n²) → O(n)
+ * PR #38: Replace indexOf-in-loop with Map-based bucket lookup
+ *
+ * Run: npx tsx packages/gea/benchmarks/sort-permutation.bench.ts
+ */
+
+function heapMB() {
+  return process.memoryUsage().heapUsed / 1024 / 1024
+}
+
+// ---------- OLD implementation (O(n²)) ----------
+function computePermutationOld(prev: any[], next: any[]): number[] {
+  return next.map((v) => {
+    const idx = prev.indexOf(v)
+    prev[idx] = undefined // mark consumed
+    return idx
+  })
+}
+
+// ---------- NEW implementation (O(n)) ----------
+function computePermutationNew(prev: any[], next: any[]): number[] {
+  const idxMap = new Map<any, number[]>()
+  for (let i = 0; i < prev.length; i++) {
+    const a = idxMap.get(prev[i])
+    a ? a.push(i) : idxMap.set(prev[i], [i])
+  }
+  const cursors = new Map<any, number>()
+  return next.map((v) => {
+    const bucket = idxMap.get(v)!
+    const cursor = cursors.get(v) ?? 0
+    cursors.set(v, cursor + 1)
+    return bucket[cursor]
+  })
+}
+
+// ---------- Benchmark harness ----------
+function bench(label: string, fn: () => void, iters: number): number {
+  // warm-up
+  for (let i = 0; i < 5; i++) fn()
+  const t0 = performance.now()
+  for (let i = 0; i < iters; i++) fn()
+  return performance.now() - t0
+}
+
+function makeArray(size: number): number[] {
+  return Array.from({ length: size }, (_, i) => i)
+}
+
+function shuffleArray(arr: number[]): number[] {
+  const a = arr.slice()
+  for (let i = a.length - 1; i > 0; i--) {
+    const j = Math.floor(Math.random() * (i + 1))
+    ;[a[i], a[j]] = [a[j], a[i]]
+  }
+  return a
+}
+
+const SIZES = [100, 1000, 5000, 10000]
+const ITERS = 200
+
+console.log('\n=== sort/reverse permutation benchmark ===')
+console.log(`${'Size'.padEnd(8)} ${'Old (ms)'.padStart(10)} ${'New (ms)'.padStart(10)} ${'Speedup'.padStart(10)} ${'Heap Δ (MB)'.padStart(12)}`)
+console.log('-'.repeat(56))
+
+for (const size of SIZES) {
+  const base = makeArray(size)
+  const shuffled = shuffleArray(base)
+
+  const h0 = heapMB()
+
+  const oldMs = bench(
+    'old',
+    () => {
+      const prev = base.slice()
+      computePermutationOld(prev, shuffled)
+    },
+    ITERS,
+  )
+
+  const h1 = heapMB()
+
+  const newMs = bench(
+    'new',
+    () => {
+      const prev = base.slice()
+      computePermutationNew(prev, shuffled)
+    },
+    ITERS,
+  )
+
+  const h2 = heapMB()
+  const heapDelta = (h2 - h1).toFixed(3)
+  const speedup = (oldMs / newMs).toFixed(1)
+
+  console.log(
+    `${String(size).padEnd(8)} ${oldMs.toFixed(2).padStart(10)} ${newMs.toFixed(2).padStart(10)} ${(speedup + 'x').padStart(10)} ${heapDelta.padStart(12)}`,
+  )
+}
+
+console.log('\nAll sizes: new implementation is O(n) vs O(n²) old.')
+console.log('Speedup scales with array size. Heap delta is minimal.\n')