⚡ Bolt: computeTaskMetrics 루프 최적화

.jules/bolt.md

@@ -4,3 +4,6 @@
 ## 2026-07-12 - Optimize renderTaskRow DOM allocations
 **Learning:** Caching unattached template nodes and instantiating them via `.cloneNode(false)` reduces DOM instantiation overhead in O(N) render loops significantly.
 **Action:** Apply this optimization to other hot-path rendering elements such as rows, cells, and stack containers.
+## 2026-08-13 - Use Float64Array instead of Map and Array.prototype for high-performance loops
+**Learning:** For high-performance O(N) loops in JavaScript, standard for loops and typed arrays (like `Float64Array`) are significantly faster than `Array.prototype` methods (`reduce`/`forEach`) and `Map` caching. They eliminate JS engine callback allocation, garbage collection, and hash-lookup overhead. Using `Int32Array` can implicitly truncate floats or `NaN`s causing logical regressions, so `Float64Array` should be the default for semantic parity with native JS Arrays.
+**Action:** Replace `reduce`/`forEach` and `Map` caching with `for` loops and `Float64Array` in hot paths.

app.js

@@ -1370,21 +1370,27 @@ function validateDateRange(startLabel, startValue, endLabel, endValue, errors) {
 }
 
 function computeTaskMetrics() {
-  // ⚡ Bolt: Cache durationDays during total calculation to avoid recalculating for every task
-  const durationCache = new Map();
-  const totalDays = state.tasks.reduce((sum, task) => {
+  const numTasks = state.tasks.length;
+  // ⚡ Bolt: Replace Map caching and reduce/forEach with Float64Array and standard for loops
+  // to eliminate callback allocation, GC pressure, and hash-lookup overhead in hot path
+  const durationCache = new Float64Array(numTasks);
+  let totalDays = 0;
+
+  for (let i = 0; i < numTasks; i++) {
+    const task = state.tasks[i];
     const duration = calculateDurationDays(task.plannedStartDate, task.plannedEndDate);
-    durationCache.set(task.id, duration);
-    return sum + duration;
-  }, 0);
+    durationCache[i] = duration;
+    totalDays += duration;
+  }
 
   const baseDate = state.baseDate;
   const byTask = new Map();
   let totalWeightedPlannedRatio = 0;
   let totalWeightedActualRatio = 0;
 
-  state.tasks.forEach((task) => {
-    const durationDays = durationCache.get(task.id);
+  for (let i = 0; i < numTasks; i++) {
+    const task = state.tasks[i];
+    const durationDays = durationCache[i];
     const weightRatio = totalDays > 0 ? durationDays / totalDays : 0;
     const plannedProgressRatio = calculatePlannedProgressRatio(baseDate, task.plannedStartDate, task.plannedEndDate, durationDays);
     const actualProgressRatio = (ACTUAL_PROGRESS_MAP[task.actualProgressStatus] || 0) / 100;
@@ -1408,7 +1414,7 @@ function computeTaskMetrics() {
       plannedDateWarning,
       actualDateWarning
     });
-  });
+  }
 
   return {
     totalDays,