⚡️ Speed up function severTiesFromParents by 41%#47
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⚡️ Speed up function severTiesFromParents by 41%#47codeflash-ai[bot] wants to merge 1 commit intoreleasefrom
severTiesFromParents by 41%#47codeflash-ai[bot] wants to merge 1 commit intoreleasefrom
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The optimized code achieves a **41% runtime improvement** (10.1μs → 7.15μs) through several targeted algorithmic optimizations: **Key Performance Improvements:** 1. **Batch Processing with Map/Set Data Structures**: Instead of processing each widget individually and updating parents repeatedly, the optimization collects all widgets that need to be removed from each parent into a `Map<parentId, Set<widgetIds>>`. This eliminates redundant parent object updates when multiple widgets share the same parent, reducing object spread operations from O(n) to O(unique_parents). 2. **O(1) Lookup Performance**: By using a `Set` for `movedWidgetsSet` and `widgetsToRemove`, the code replaces O(n) array `.filter()` operations with O(1) `.has()` checks. This is particularly impactful in the children filtering loop where the line profiler shows 15.6% time spent on widget lookups. 3. **Single-Pass Filtering**: The children array filtering now uses a manual loop with Set lookups instead of `.filter()` with repeated searches, avoiding closure overhead and improving cache locality. 4. **Early Bailout Optimization**: The code checks if `updatedChildren.length === prevParent.children.length` to skip updates when no actual changes occurred, preventing unnecessary object spreads and layout deletions. 5. **Efficient Array Building in `deleteWidgetFromPreset`**: Replaced `.map().filter()` chain (two passes) with a single loop that only adds valid entries, eliminating intermediate array allocations and the empty object creation pattern. **Test Case Performance:** - Edge cases with empty/falsy inputs see **50-70% improvements** due to early returns - The large-scale test (500 widgets, 300 moved) benefits most from the batching optimization, as multiple widgets per parent are common - Basic functionality tests show modest gains as they have few widgets, but the correctness is preserved **Why This Works:** The profiler shows the hot path is in widget lookups (lines 68-79), consuming ~70% of total time. By using Set-based lookups and batching updates per parent, the optimization reduces both algorithmic complexity and allocation overhead, directly targeting the bottleneck revealed by line profiling.
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📄 41% (0.41x) speedup for
severTiesFromParentsinapp/client/src/layoutSystems/anvil/utils/layouts/update/moveUtils.ts⏱️ Runtime :
10.1 microseconds→7.15 microseconds(best of10runs)📝 Explanation and details
The optimized code achieves a 41% runtime improvement (10.1μs → 7.15μs) through several targeted algorithmic optimizations:
Key Performance Improvements:
Batch Processing with Map/Set Data Structures: Instead of processing each widget individually and updating parents repeatedly, the optimization collects all widgets that need to be removed from each parent into a
Map<parentId, Set<widgetIds>>. This eliminates redundant parent object updates when multiple widgets share the same parent, reducing object spread operations from O(n) to O(unique_parents).O(1) Lookup Performance: By using a
SetformovedWidgetsSetandwidgetsToRemove, the code replaces O(n) array.filter()operations with O(1).has()checks. This is particularly impactful in the children filtering loop where the line profiler shows 15.6% time spent on widget lookups.Single-Pass Filtering: The children array filtering now uses a manual loop with Set lookups instead of
.filter()with repeated searches, avoiding closure overhead and improving cache locality.Early Bailout Optimization: The code checks if
updatedChildren.length === prevParent.children.lengthto skip updates when no actual changes occurred, preventing unnecessary object spreads and layout deletions.Efficient Array Building in
deleteWidgetFromPreset: Replaced.map().filter()chain (two passes) with a single loop that only adds valid entries, eliminating intermediate array allocations and the empty object creation pattern.Test Case Performance:
Why This Works:
The profiler shows the hot path is in widget lookups (lines 68-79), consuming ~70% of total time. By using Set-based lookups and batching updates per parent, the optimization reduces both algorithmic complexity and allocation overhead, directly targeting the bottleneck revealed by line profiling.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
📊 Performance Profile
View detailed line-by-line performance analysis
To edit these changes
git checkout codeflash/optimize-severTiesFromParents-ml27k7rsand push.