UX Testing
Guerrilla usability testing is informal, rapid feedback collection from whoever is available — strangers in a coffee shop, colleagues in the hallway, people at a meetup. It trades rigor for speed and cost, making it ideal for early-stage products or quick validation before investing in more structured research. Done right, a
UX Testing
Usability testing is the practice of watching real users attempt to complete tasks with your product, then using what you observe to fix what doesn't work. It's distinct from functional QA — it measures whether users can accomplish their goals, not whether the software does what the
Test Reliability
Flaky tests are hard to detect manually — a test that fails 5% of the time looks like noise until someone tracks it across 20 CI runs. GitHub Actions gives you tools to surface flaky tests automatically: test annotations that appear directly on pull requests, workflow features for re-running failed jobs,
API Testing
Frontend development has a classic blocking problem: the backend isn't ready. You're building a checkout flow, but the payments API returns a 500. You want to test the empty state, but the backend always returns data. You need to simulate a 429 rate limit, but production
API Testing
You can't write a test for every possible input. A string field accepts billions of values. A numeric parameter has edge cases you haven't considered. An API that looks solid against your 20 hand-written test cases might crash on the 21st input — the one a real
API Testing
Writing API tests by hand means writing a lot of boilerplate: constructing URLs, setting headers, serializing request bodies, parsing responses. When the API changes, you update the tests manually and hope you caught every callsite. OpenAPI Generator eliminates that boilerplate. Given an OpenAPI spec, it generates a fully typed API
API Testing
Both Dredd and Schemathesis test whether your API implementation matches its spec. Both read OpenAPI (or API Blueprint) definitions and make real HTTP requests. Beyond that, they take fundamentally different approaches — and understanding the difference determines which one belongs in your pipeline. The Core Difference Dredd is deterministic. It reads
API Testing
API contracts are promises. Your OpenAPI specification says "this endpoint returns a userId field of type string." Every consumer of your API — mobile apps, partner integrations, frontend teams — builds against that promise. When the promise breaks silently, you get production incidents, not compiler errors. Spectral is a linter
Test Reliability
Cypress flaky tests are particularly frustrating because Cypress has automatic waiting built in — so why are tests still timing out? The answer is usually one of three things: the test is waiting for the wrong thing, network requests are unpredictable, or state leaks between tests. This post walks through each
API Testing
Most teams write code first, then document it. The API exists; you write the OpenAPI spec to describe what you built. This approach has a persistent problem: the code and the documentation diverge. Consumers get specs that don't match the real behavior. Tests get written against the implementation,
Testing
End-to-end tests are slow by nature — they launch browsers, navigate real pages, wait for network. A 400-test Playwright suite can take 20-30 minutes on a single runner. Sharding splits those tests across multiple workers and brings that down to 5-8 minutes. Here's how to configure it on GitHub
Testing
pytest-xdist lets you run tests across multiple CPUs — or even multiple machines — without changing a single test. A 10-minute suite can drop to 2-3 minutes with 4 workers. Here's how to set it up correctly, including the database isolation patterns that trip up most teams. Installation pip install