Infinite scroll is a popular feature in modern web applications, powering everything from social media feeds to product catalogs. It creates a smooth user experience but also brings unique challenges for QA engineers such as verifying that items load progressively, ensuring API calls trigger correctly, and handling rapid scrolling without glitches. In this post we will explore a demo infinite scroll app and show how to automate its testing with Playwright, covering everything from initial load checks to end of list validation.

The Demo App: Infinite Scroll in Action

Before diving into the tests, let's take a closer look at the demo application we will be working with. The goal of the app is simple: display a list of items that continuously loads as the user scrolls down. While the implementation is lightweight, it includes many of the same behaviors you would find in real production systems.

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The main parts of the page are:

• Container with a scrollable list: The central feature of the demo is a fixed-height container that can be scrolled independently of the rest of the page. Items are dynamically added into this container in batches of twenty until the total limit of one hundred is reached.
• Loading indicator and spinner: Whenever new items are being fetched, a loading section becomes visible at the bottom of the container. It includes a spinner animation and a message that says “Loading more items…” which clearly communicates that the system is busy retrieving more data.
• End of list message: Once all one hundred items are loaded, the loading indicator is replaced with a final message that says “You've reached the end! All items have been loaded.” This makes the user experience clear by showing that there is no more content to scroll for.
• Stats panel: A floating stats panel is fixed to the top right of the page. It shows three key values: the number of items currently loaded, the total number of available items, and the number of API calls made. This panel is especially useful during testing because it gives instant feedback on the internal state of the application.

Beyond the visible elements, the demo app also simulates realistic conditions. Items are fetched in pages with a short delay to mimic network latency, and there is even a small chance of an API failure being triggered. These extra touches make the demo behave much more like a real system and provide plenty of scenarios for automation tests to cover.

Challenges in Testing Infinite Scroll

Testing infinite scroll can be trickier than it looks. Unlike a traditional paginated view where the next set of items is triggered by a clear user action such as clicking a “Next” button, infinite scroll relies on background logic that fires automatically as the user moves through the page. This introduces a number of challenges that QA engineers need to address.

• Non deterministic behavior: Network conditions and asynchronous operations mean that items do not always load at the same speed. Sometimes the response arrives almost instantly, other times it takes longer, and occasionally it may fail. Automation tests need to account for these variations by using smart waits and robust conditions rather than fixed delays.
• Progressive loading without duplication: Each scroll should add a new batch of items to the list. If the logic misfires, the user might see duplicate entries or missing items. A solid test strategy should confirm that the items are added in the correct order, without repeats, and that the number of items always matches the expected count.
• Detecting the end of the list: At some point there is nothing left to load. The application should show a clear message and stop making new API calls. Tests must verify that this end condition appears exactly when the limit is reached and that no further requests are triggered.
• Verifying API call counts: Every time a new batch is loaded, a corresponding API request should be made. Keeping track of these calls helps ensure that the backend and frontend are working together correctly. The demo app exposes the number of API calls in the stats panel, making it easy to validate this in automation.
• Handling rapid user interactions: Real users do not always scroll at a steady pace. Some may flick quickly to the bottom, others may hover and pause. The system must handle both cases gracefully. A common bug in infinite scroll is multiple API calls firing at once during fast scrolling, leading to inconsistent results. Automated tests should confirm that only the correct number of requests are made no matter how the scrolling is performed.

These challenges highlight why infinite scroll requires more than simple assertions about visible elements. The tests need to capture both the dynamic nature of the interface and the correctness of the data flow behind it.

Writing and Walking Through the Test Cases

The Playwright test file is organized to cover every important scenario that an infinite scroll implementation should handle. Each category of tests focuses on a particular aspect of the experience, and together they form a complete safety net for verifying functionality.

The journey begins with the initial load. When the page is first opened, the application should display the first batch of items, and the counters in the stats panel should immediately reflect that at least some items are present. This ensures the application starts in a valid state.

                
const initialItems = await page.locator('[data-testid^="item-"]').count();
expect(initialItems).toBeGreaterThan(0);
expect(initialItems).toBeLessThanOrEqual(20);

const loadedCount = await page.locator("#loaded-count").textContent();
expect(parseInt(loadedCount)).toBeGreaterThan(0);

const apiCalls = await page.locator("#api-calls").textContent();
expect(parseInt(apiCalls)).toBe(1);
                

After verifying the starting conditions, the focus shifts to scroll-triggered behavior. As soon as the bottom of the container is reached, the loading section should become visible, complete with the spinner and the loading text.

                
await page.locator("#listContainer").evaluate(el => {
  el.scrollTop = el.scrollHeight;
});

await expect(page.locator("#loading")).toBeVisible();
await expect(page.locator(".loading-spinner")).toBeVisible();
await expect(page.locator("#loading p")).toHaveText("Loading more items...");
                

The next check confirms that new items are appended to the list when the scroll reaches the bottom. The number of items must increase and the count of API calls should rise by one.

                
const initialCount = await page.locator('[data-testid^="item-"]').count();
const initialApiCalls = parseInt(await page.locator("#api-calls").textContent());

await page.locator("#listContainer").evaluate(el => {
  el.scrollTop = el.scrollHeight;
});

await page.waitForFunction(expected =>
  document.querySelectorAll('[data-testid^="item-"]').length > expected,
  initialCount
);

const newCount = await page.locator('[data-testid^="item-"]').count();
expect(newCount).toBeGreaterThan(initialCount);

const newApiCalls = parseInt(await page.locator("#api-calls").textContent());
expect(newApiCalls).toBe(initialApiCalls + 1);
                

Progressive loading ensures that multiple scrolls add new batches one after the other. This simulates a user browsing through longer feeds and helps validate that the list continues to expand without interruption.

                
for (let i = 0; i < 3; i++) {
  await page.locator("#listContainer").evaluate(el => {
    el.scrollTop = el.scrollHeight;
  });

  await page.waitForFunction(count =>
    document.querySelectorAll('[data-testid^="item-"]').length > count,
    await page.locator('[data-testid^="item-"]').count()
  );
}
                

Edge conditions are equally important. When all one hundred items are loaded, the end message must appear and the app should stop making new requests. Conversely, if the user scrolls only halfway down, nothing should happen until the bottom is reached.

                
await expect(page.locator("#endMessage")).toBeVisible();

await page.locator("#listContainer").evaluate(el => {
  el.scrollTop = el.scrollHeight * 0.5;
});
await page.waitForTimeout(2000);
await expect(page.locator("#loading")).not.toBeVisible();
                

Another layer of validation involves checking that items are loaded in the correct order and contain the right content. This ensures that the sequence is consistent and no duplicate entries are introduced.

                
const items = await page.locator('[data-testid^="item-"]').all();
const itemTitle = await items[0].locator("h3").textContent();
expect(itemTitle).toBe("Item 1");

const itemId = await items[0].getAttribute("data-item-id");
expect(parseInt(itemId)).toBe(1);
                

Finally, the stats panel acts as a reliable source of truth. The loaded item count shown to the user must always match the number of elements in the DOM, and the API call counter should be accurate.

                
const loadedCount = parseInt(await page.locator("#loaded-count").textContent());
const actualCount = await page.locator('[data-testid^="item-"]').count();
expect(loadedCount).toBe(actualCount);
                

By walking through each of these cases, the test suite achieves both breadth and depth. It covers the smooth flow of a user scrolling gradually through content, the fast interactions of a user flicking to the bottom, and the edge conditions that define when the system should stop. Together, these tests provide confidence that the infinite scroll behaves reliably under different scenarios.

Best Practices for Infinite Scroll Testing

Automating infinite scroll comes with a unique set of challenges, and following a few best practices makes the process much more reliable. One of the most important techniques is using waitForFunction to check for changes in the DOM instead of relying on fixed waits. Since content loads asynchronously, waiting for a condition such as “the number of items is greater than before” ensures the test only proceeds once the page is actually ready.

Timeouts are another factor that should be handled carefully. Adding them generously provides enough time for slower responses or network delays, but they should not be excessive. A smart balance allows the tests to stay stable without making them unnecessarily long.

When simulating user actions, it is valuable to test both gradual scrolling and rapid scrolling. Real users interact with applications in different ways, and infinite scroll should handle both patterns gracefully. Tests that mimic fast flicking to the bottom of the list can catch issues such as multiple duplicate requests, while slower scrolling validates that batches load progressively.

Validation should not stop at the visible interface. The frontend state, like a spinner appearing and disappearing, is important, but so is the backend effect. Checking the API call counter ensures that the system is making the right number of requests at the right time, giving confidence that the data pipeline is functioning correctly.

Finally, keeping test data deterministic wherever possible makes debugging much easier. In the demo application, the total number of items is fixed, and the structure of each batch is predictable. This helps create stable tests that consistently verify expected outcomes. In real applications, controlling data fixtures and using mock responses can provide the same benefit.

Together, these practices help make infinite scroll tests both robust and maintainable, turning what could be a flaky area of automation into a reliable part of the test suite.

Conclusion

Infinite scroll is a powerful feature that can greatly improve the user experience, but it also introduces complexities that demand thoughtful testing. By breaking the problem into clear scenarios—initial load, progressive loading, edge conditions, and rapid interactions—it becomes possible to design tests that reflect how real users interact with the application. Playwright's ability to handle dynamic content, combined with good practices like condition-based waits and realistic simulations, makes it a strong choice for this type of automation.

The demo application and its test suite demonstrate how these ideas can be applied in practice, showing not only how to validate the user interface but also how to confirm the accuracy of backend interactions. With this foundation, we can confidently extend the same approach to more complex production systems such as e-commerce product listings, news feeds, or dashboards.

For those who want to explore further, the complete code examples along with the demo application are available on our GitHub page. See you in the next one!