Research guide
How to Test Paginated Tables End-to-End
Paginated tables hide bugs behind page transitions: off-by-one counts, lost filters, broken next buttons, and state that resets when the user changes pages. This guide covers the cases that expose those failures.
Why pagination is tricky
Pagination looks boring until the page boundary breaks. Then the table shows the wrong slice of data, the next button lies about whether more rows exist, or a filter disappears when the user advances to page two.
That is why a table test has to move through pages, not just inspect the first page.
Core cases
Cover the first page, a middle page, the last page, next and previous navigation, changing the page size, and jumping directly to a page number if the UI allows it.
Then repeat the same cases with a search term or filter applied. A pagination control that works only on the unfiltered view is not production-ready.
What to assert
Assert the row count, the active page number, the disabled state of previous and next controls, and that the expected row appears on the expected page.
If the table is server-driven, assert the API query includes the page and size you selected. That catches mismatches between the UI and the backend.
The common failure modes
Off-by-one page counts, stale page state after filtering, duplicate rows across pages, and controls that stay clickable after the end of the dataset are the bugs that make pagination look flaky even when the data is fine.
How CueTest helps
A good prompt is outcome-first: “Open the customer list, go to page three, switch the page size to 25, and verify the target record still appears when sorted by newest.”
CueTest keeps the failed step and screenshots, which makes it easier to see whether the bug is the data, the controls, or the page state.
Key takeaways
- Pagination tests should cover first, middle, and last pages, plus page-size changes.
- Repeat pagination cases with search and filters applied.
- Assert row counts and control states so page boundaries cannot lie.