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Subito’s case study reports that opening a React Brand filter with about 1,175 options took 1,256 ms of INP in a local Chrome DevTools test. After the team virtualized the list—rendering only visible rows and a small buffer—the reported reading fell to 96 ms. The improvement illustrates how mounting fewer off-screen options can help a slow dropdown; it is not a guarantee that another list or device will see the same result.
Why the Brand dropdown became slow
Subito used a shared custom MultiSelect, described by the case-study authors as a reskinned react-select component. Filters with roughly a dozen choices worked acceptably. On a Shoes category page, however, the Brand (“Marca”) filter exposed around 1,175 options while its menu viewport showed only about six rows.
According to Giovanni Tramutola and Alessandro Grosselle’s 2025 case study, opening that unvirtualized menu synchronously created about 1,175 Option components, each containing a label and custom checkbox, before the browser could paint the menu. The authors identified that work as the source of the long interaction. Google notes that large DOMs can make rendering updates more expensive and delay presentation of the next frame, although that general guidance does not independently establish the cause or exact improvement in Subito’s test. Google’s guidance on DOM size and interactivity.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe authors also make a useful distinction: “A list of 1,100 items is not inherently a performance problem.” The concern is doing unnecessary rendering work at the moment the user opens it, especially when nearly all rows are outside the visible area.
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What the INP readings mean—and what they do not
Interaction to Next Paint (INP) measures the latency from a qualifying interaction until the browser can paint the next frame. It accounts for input delay before event handlers begin, processing time while callbacks run, and presentation delay before the frame appears. Clicks, taps, and keyboard interactions can contribute; a page’s INP reflects interaction responsiveness across a visit. Google’s INP guidance.
Google classifies INP at or below 200 ms as good, above 200 ms through 500 ms as needing improvement, and above 500 ms as poor. Those thresholds are assessed at the 75th percentile of page loads, separately for mobile and desktop. Google states, “An INP below or at 200 milliseconds means a page has good responsiveness.”
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For Subito’s specific test, the case-study authors report a local Chrome DevTools reading of 1,256 ms before the change and 96 ms after it, using a mobile viewport and 4× CPU slowdown. Afterward, they counted 13 rendered [role="option"] nodes. The article does not specify the handset model, browser version, sample or repeat count, or a full test protocol; the figures are the authors’ local readings, not independent replication or field data. They should not be treated as a result every dropdown, device, or real-world visit will reproduce.
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How windowing reduced the work
The reported fix was a custom useVirtualScroll hook. Instead of mounting every option, it rendered the visible slice plus a five-item overscan buffer—extra rows just outside the viewport to make scrolling feel continuous. A spacer preserved the full list’s scroll height even though most option elements were not mounted at once.
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The case study describes measuring an option’s height after mount, calculating the total list height, deriving visible start and end indices from the scroll position, and positioning that slice within the scrolling area. With a viewport showing about six rows and five extra items in the buffer, the list could remain scrollable while keeping the rendered option count small. The reported post-change count was 13 option nodes.
This reduces the number of components the browser must create and update when the menu opens. It does not make the underlying catalog disappear: the implementation keeps the full list available for scrolling and custom searching, while limiting which option elements are present in the DOM.
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Choose fixed-height arithmetic or measured rows
The simple approach depends on every row having the same height. If that assumption holds, an index and one row-height value are enough to estimate where each visible item belongs. When content height varies, the index-to-position arithmetic can become inaccurate.
| Approach | When it fits | Trade-off |
|---|---|---|
| Fixed-height window with index arithmetic | Rows are reliably uniform in the supported layouts. | Simple to implement, but wrapping labels, headers, font changes, or resizing can cause gaps, overlap, scroll drift, or unreachable options. |
| Measure variable-height rows | Rows can have different heights or change with layout. | More measurement and maintenance work is needed to keep positions accurate. The case study provides no head-to-head benchmark against the fixed-height approach. |
Group headers, labels that wrap on narrow screens, font loading, device rotation, resizing, and density changes can all invalidate a fixed row-height assumption. Keep rows uniform where the product permits; otherwise measure row heights or use a virtualization library that supports variable-height content. The small custom hook is not a universal substitute for a library.
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Account for search and accessibility behavior
Windowing removes off-screen options from the DOM. As a result, browser-native Ctrl+F cannot find an option that is not currently rendered. If users need to find a brand anywhere in the catalog, provide a custom search that checks the full option data and brings a match into the rendered window. The case study says the full list remains available to custom searching even though only a slice is mounted.
Because the case study reports option-node counts and uses role="option", verify the finished component’s keyboard and assistive-technology behavior as well as its speed. Test focus movement, selection, and announcements with the menu open and while the rendered window changes; a smaller DOM alone does not establish that the interaction remains accessible.
Quick Recap
How to validate a similar change
- Reproduce the slow interaction. Open the large filter under the same viewport and CPU-throttling conditions you intend to compare, and record the setup.
- Check the work on opening. Inspect how many option components and DOM nodes are created before the menu appears, and identify whether rendering all rows is the dominant cost.
- Apply a window only if it fits the layout. For uniform rows, render the visible range plus a modest overscan and preserve the scrollable list’s total height. For variable rows, use measurement rather than assuming a single height.
- Test edge cases. Check the narrowest supported width, long labels, group headers, font loading, resize, rotation, scrolling to the end, search results outside the current window, and keyboard operation.
- Compare consistently, then check real users. Repeat the local test with the same conditions before and after, but treat lab results as diagnostic evidence. Field INP is assessed at the 75th percentile separately for mobile and desktop, so a local DevTools number is not a substitute for real-user data.
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