Discussions

A lot of focus in API testing goes into making sure the happy path works — the request is valid, the response is correct, and everything lines up with the spec. But in production, what often causes issues are the unexpected, malformed, or borderline inputs: invalid query params, missing headers, weird encodings, strange date formats, or requests sent in the wrong order.

These “unhappy paths” are harder to think of and even harder to test consistently. Most teams write a few negative test cases manually, but there’s no guarantee that they reflect the strange things real users (or bots) might actually send.

One way teams are closing this gap is by analyzing real traffic — looking at logs, error reports, or captured requests — and turning those into test cases. This helps surface edge cases that weren't thought of during initial test design. Tools like Keploy support this approach by capturing real API behavior, including failing and edge-case requests, and converting them into reproducible tests.