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The latest News and Information on Software Testing and related technologies.

The Missing Step in Mobile Release Operations: Store Screenshot Management

Mobile release teams are used to managing code, builds, test results, signing credentials and deployment approvals. Store screenshots often sit outside that system. They are treated as a final design request, passed between product, marketing and engineering in a collection of chat messages and shared folders.

Make Failure Boring with Mocks

Every codebase has a failure path nobody has run. Not through laziness, but because reproducing it requires a backend dependency to misbehave on cue. In the package notifier, the carrier must refuse, stall, or return nonsense at the exact moment the test runs. So the retry logic ships unverified and everyone hopes. The seam from post 2 already gives the test control. A seam is a place where you can change what code does without editing that code.

Test Behavior, Not Choreography

The spy from post 4 is a sharp tool. Once a test can record every interaction, it is tempting to assert on all of them. The result looks thorough, but it is usually a transcript rather than a useful specification. This post takes a test written that way, makes a change that no customer could possibly notice, and watches the test fail anyway. This is part 5 of a ten-part series. The code is in Java, Node.js, Go and Python.

Application Level Dependency Chaos Testing

Somewhere in your service is a branch that has never executed. Not a rare one, a never one. It handles a dependency being unavailable: it reads from a cache, it returns a stale value, it marks the response degraded so callers know not to trust it too far. It was written carefully. It was reviewed. Whether it works is an open question, because nothing in the test suite makes that dependency fail, and the dependency does not fail on request.

Break One Dependency, Not The Whole Cluster

Scoped chaos rules are now in proxymock. A filter query picks the traffic, an effect perturbs it, and every response that gets touched is labelled so you can tell an injected failure from a real one for the rest of the run. Available in v2.5.892 and newer. The short version of why: kill a pod and you learn something real, but you do not learn what your service does when a dependency stays up and starts lying to it.

Solusec Review: Penetration Testing

Cyber insurers now routinely ask smaller organisations for evidence of penetration testing before they'll even quote a premium. That single requirement has pushed a lot of businesses, charities and schools into a market they don't understand, full of firms whose "testing" amounts to running a vulnerability scanner and printing the results. Knowing who's actually doing manual, accredited work versus who's reselling automated output matters more than most buyers realise until they're staring at a report full of generic findings.

Run Playwright Tests with Harness AI Test Automation | CI/CD + AI Failure Analysis

End-to-end testing should not slow your delivery pipeline down. But for many teams, Playwright test suites still live in disconnected jobs, produce noisy failures, and make it hard to tell whether a failed test is a real regression, a flaky test, or just another false positive. In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, shows how Harness AI Test Automation helps teams run, analyse, and trigger Playwright tests directly from their software delivery workflows.

Better context, smarter testing: How to give your AI coding agent direct access to k6 docs

As testing workflows become more AI-assisted, fast access to accurate documentation matters more than ever. Whether you're writing a new load test, troubleshooting an issue, or having an AI agent generate a script for you, you need reliable guidance that keeps pace with the way you work. But most documentation still lives in a browser. Every time you or your agent needs to verify an API or look up a best practice, you're forced to leave your terminal or editor and interrupt your workflow.

Building a Fiber Optic Testing Workflow: Inspection, Loss Testing, and Troubleshooting

A fiber link can look perfectly intact and still misbehave the moment traffic hits it. The gap between a cable that appears fine and one that actually performs comes down to how it was checked before handover. This article walks through a practical sequence for confirming that a link is ready for service, covering what to verify beforehand, how to prepare connections, which measurements matter, and how to turn the results into a decision.