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

9 Best AI Penetration Testing Companies for Enterprise Security Teams

Enterprise security teams know the value of penetration testing. The problem is the schedule. A large organization may run hundreds of web applications, thousands of API endpoints, mobile apps, AI features, and a sprawling external attack surface, and much of it changes every week. An annual or quarterly pentest examines a snapshot of that environment, produces a report weeks later, and leaves most of the year untested.

Test Your MySQL 8.4 Upgrade With Real App Queries

Before you start, paste this into Claude Code, Cursor, Codex, Gemini CLI, Kiro, or any assistant that can read a URL and run commands: The install-speedscale skill installs proxymock for your operating system and walks you through proxymock init. It stops when you need to complete browser sign-in, keeps your recordings on your machine, and connects the proxymock MCP server so your assistant can run the prompts later in this article.

Why Mocks Fail at Scale #softwareengineering #devops #softwaretesting #api #aicoding

Mocking for testing starts off easy, but once you scale to multiple teams and AI agents, handcrafted mocks become a serious form of technical liability. Instead of treating mocking as an individual software engineering task, shift your mindset to treat it as a platform engineering task focused on automation and continuously refreshed modern data. Watch to see how adopting technologies like traffic replay to simulate realistic backend sandboxes can transform your modern testing workflow!

How to monitor Cypress tests with Grafana Cloud

If your Cypress suite has tests that fail more often or run slower, you know it can be hard to figure out the pattern from a single job. It could be one spec that slowed down, or a single test that fails, or maybe the entire suite is trending slower. The root cause could be a bug in the app, or a flaky test, or something else.

Continous ORT Testing with Harness

Most Operational Readiness Testing (ORT) programs follow the same ritual. A checklist gets filled out. Someone runs a load test in a war room the week before launch. A failover drill gets scheduled, and everyone hopes it goes cleanly. Then the release is shipped, and testing is done. But with Harness, you can make this process continuous, and your service resilience is protected by the same ORT checklist for every small change in your SDLC.

Monitor test health at a glance in Bitbucket Tests

When a team relies on automated tests in CI/CD, knowing that tests ran is only the beginning. Understanding whether the suite is healthy, which tests need attention, and how a specific test has behaved over time — that’s what drives action. Bitbucket Tests is evolving to make those answers easier to find and give you tools to improve your test health.

Improvise your Operational Readiness Testing (ORT) with Harness

Most Operational Readiness Testing (ORT) programs follow the same ritual. A checklist gets filled out. Someone runs a load test in a war room the week before launch. A failover drill gets scheduled, and everyone hopes it goes cleanly. Then the release is shipped and testing is done. But with Harness you can make this process continuous and your services resilience is protected with the same ORT check list with every small change that is happening in your SDLC.

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.