⚡ Bolt: computeTaskMetrics 루프 성능 최적화

.jules/bolt.md

@@ -1,6 +1,11 @@
 ## 2026-07-12 - O(N) penalty with Array.shift() in queues
 **Learning:** In Kahn's topological sort and similar algorithms, using `queue.shift()` inside a while loop causes an O(K) penalty per iteration since the entire remaining array needs to be shifted in memory, turning an O(V+E) algorithm effectively into O(V^2+E) worst case.
 **Action:** Always replace `queue.shift()` with a tracking pointer (e.g., `let queueIndex = 0; queue[queueIndex++]`) when using JavaScript arrays as queues in performance-critical graph algorithms.
+
 ## 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.
+
+## 2026-08-23 - Optimize array processing in computeTaskMetrics
+**Learning:** In high-frequency render paths, `Array.prototype.reduce`/`forEach` and `Map` cache structures add noticeable JS engine callback allocation, garbage collection, and hash-lookup overhead.
+**Action:** Replace them with standard `for` loops and typed arrays (e.g., `Int32Array`) to improve O(N) iteration performance when arrays and arrays lengths are known and fixed.

app.js

@@ -1370,21 +1370,26 @@ 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) => {
+  // ⚡ Bolt: Replace Map with Int32Array and Array methods with for loops to eliminate JS engine callback allocation, garbage collection, and hash-lookup overhead
+  const tasksLen = state.tasks.length;
+  const durationCache = new Int32Array(tasksLen);
+  let totalDays = 0;
+
+  for (let i = 0; i < tasksLen; 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 < tasksLen; 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 +1413,7 @@ function computeTaskMetrics() {
       plannedDateWarning,
       actualDateWarning
     });
-  });
+  }
 
   return {
     totalDays,