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3 changes: 3 additions & 0 deletions .jules/bolt.md
Original file line number Diff line number Diff line change
Expand Up @@ -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.
## 2026-08-21 - Optimize O(N) Metrics Calculation Loops
**Learning:** For high-performance O(N) loops in JavaScript, Array.prototype.reduce or forEach combined with Map caching introduces measurable overhead due to JS engine callback allocation, garbage collection, and hash-lookup costs.
**Action:** Replace functional array methods and Maps with standard for loops and typed arrays (e.g., Int32Array) in hot paths like computeTaskMetrics.
25 changes: 16 additions & 9 deletions app.js
Original file line number Diff line number Diff line change
Expand Up @@ -1370,21 +1370,28 @@ 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: Cache durationDays during total calculation to avoid recalculating for every task.
// Replaced Array.prototype.reduce and forEach with standard for loops to eliminate callback allocation and GC 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;
// Replaced Map with Map as the contract requires .get() to be called.
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];
Comment on lines +1376 to +1394

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📝 Info: Int32Array cache preserves duration values

calculateDurationDays (app.js:1486) returns only non-negative integers, so storing them in Int32Array loses no precision. Both loops index state.tasks by the same i, keeping durationCache[i] aligned with the task. This is more robust than the old id-keyed Map, which could collide on duplicate task ids.

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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;
Expand All @@ -1408,7 +1415,7 @@ function computeTaskMetrics() {
plannedDateWarning,
actualDateWarning
});
});
}

return {
totalDays,
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