Software testing test automation tutorials and videos

Rethinking Software Quality: a New Approach to Testing API

Software Testing Magazine — Fri, 09 Oct 2026 14:20:20 +0000

This session, “Rethinking Software Quality: Why API Testing Needs to Change,” unpacks the challenges of testing API-driven ecosystems, the limitations of conventional QA, and the new pressures created by AI and evolving digital platforms. It introduces a fresh approach to software quality, one that leverages agentic orchestration, multimodal testing, and intelligence-driven automation to transform how teams ensure quality at speed and scale. APIs are the backbone of today’s digital economy, powering everything from mobile apps to enterprise systems. Yet, as reliance on APIs grows, so do the risks: a single API failure can disrupt entire businesses. Traditional QA strategies are no longer enough to ensure resilience, security, and scalability in this new landscape. Modern API testing faces a range of complex challenges due to the evolving landscape of software development, cloud-native architectures, and the increasing reliance on APIs for seamless integration. Here is an overview of the key challenges of API testing,: 1.Diverse API Protocols and Standards: APIs come in various forms (REST, GraphQL, gRPC, SOAP, etc.), each with unique characteristics and different testing approaches 2.Microservices and Distributed Systems: Microservices architectures split functionality into independent services, leading to integration complexity and sService dependencies 3. APIs Security Vulnerabilities: API are prime targets for attacks (e.g., SQL injection, authentication flaws, rate limiting). 4.APIs Performance and Scalability : you must handle high traffic, latency, and concurrency which and lead to slow response times under load and resource exhaustion (e.g., database locks, memory leaks). 5.Data Management and Test Data: realistic test data is hard [...]

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Playwright for WordPress: A Practical Guide to Automating End-to-End Tests

Software Testing Magazine — Tue, 06 Oct 2026 16:27:02 +0000

Stop shipping browser bugs when you update your WordPress website. This article explains how to set up Playwright automated tests for WordPress, from saved logins to continuous integration, before the next update. Author: Samrat Biswas, Unified Infotech Private Limited Imagine, your team ships a new landing page, tests it in Chrome, and finally launches it. Everything is fine until you receive a support email. A customer on Safari is unable to submit a signup form. One of your team members opens Firefox to check and notices the dropdown menu doesn’t even open. Nobody saw that coming, as every test, every single time, ran in one browser. The site worked, but it just did not work on every browser. This is one of the most common problems in WordPress QA, and Playwright for WordPress can solve this problem. Chromium, Firefox, and WebKit render pages and run scripts differently, so a test suite built around one browser will catch some bugs, but not browser-specific compatibility issues. Playwright runs the same test across all three browsers from one codebase using configuration. It automates the clicks, form fills, and page checks, eliminating the need for a human tester. Why Use Playwright for WordPress E2E Testing? A WordPress site often combines themes, custom JavaScript, APIs, plugins, page builders, forms, and third-party services. Testing everything with traditional E2E testing becomes complicated. Traditional testing frameworks that may depend on separate browser drivers can easily break after major browser updates. Asynchronous REST API calls and page builder scripts [...]

The post Playwright for WordPress: A Practical Guide to Automating End-to-End Tests first appeared on Software Testing Magazine.

The Next Software Testing Platform Will Be Built by Customers

Software Testing Magazine — Thu, 01 Oct 2026 10:21:02 +0000

Code generation with AI tools is rapidly expanding in the software development world. The software testing and QA activities are also impacted by this trend. What does it mean for suppliers of test automation tools? In this article, Maz Daly explains how they should transition from turnkey solutions to providing a platform that allows customers to build their own software testing platform with confidence and scale. Author: Maz Daly, Chief Marketing Officer at Leapwork. Much of the testing market is selling yesterday’s platform with tomorrow’s AI language while customers are already experimenting with AI, code, and other tools to build what their applications and workflows require. The testing market has entered a sea of sameness. Across the category, vendors map features to analyst criteria, assemble Frankenstein platforms from acquired components, and wrap familiar functionality in agentic claims. Buyers encounter increasingly similar stories about what AI makes possible and increasingly long lists of capabilities designed to satisfy a market report. Meanwhile, the source of innovation is shifting. Development teams can use AI, code, Selenium, Playwright, and other tools to create testing capabilities tailored to their applications and workflows. They can build functional tests, expand regression coverage, validate business processes, and automate quality practices with a level of specificity that a standard product roadmap cannot anticipate. Creation, however, is only the first step. As those capabilities scales across an enterprise, they need a system around them: expertise to design and maintain coverage, standards and guardrails to keep teams aligned, evidence leaders can [...]

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Silent Protection Failures: When Every Test Passes and the User Is Still Exposed

Software Testing Magazine — Mon, 21 Sep 2026 21:39:23 +0000

A privacy product tells a user that her personal data has been removed from data broker sites. Every test in the suite passed. Was the data removed? Most test suites cannot answer that question, and this article explains why, and what to do about it. Author: Yevheniia Sakovets, https://yevheniiasakovets.com/ Consumer privacy and security software makes a specific kind of promise. It does not promise a feature; it promises that something happened. Your data was deleted. Your password is encrypted. Your files were wiped. Your credentials have not appeared in a breach. The user cannot check any of these claims. That is the whole reason she bought the product. I have spent the last year owning quality for exactly this kind of software, and before that thirteen years verifying data as it moved across systems in fintech, e-commerce, medical devices, and a loyalty platform with tens of millions of users. The defect class described here is the one that worries me most, because it does not look like a defect. It looks like success. I call it a silent protection failure: the software reports that a protective operation has completed, and it has not. Why every test passes anyway Think about how a deletion request actually travels. The user enters her name, email, and address in the interface. The interface sends that to an API. The API hands it to a backend service. The backend builds a request to an external party, in this case a data broker, and sends it. [...]

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Your AI Doesn’t Know What Is “Correct”

Software Testing Magazine — Mon, 14 Sep 2026 16:50:01 +0000

AI-assisted code generation has changed the capabilities of organizations to produce code. In this article, Hélder Ferreira discusses the impact on software quality created by this new situation. The main problem is that this new code is often created by tools that lack the knowledge of the global context of both the application infrastructure and the process being automated. Using functional tests as a baseline might help to limit the risks. Author: Hélder Ferreira, Director of Product Management, Sembi, https://www.sembi.com/ Everyone knows that AI “speeds” up development. Recent research found that developers using AI tools increased their coding activity, measured by commits, by as much as 180%. But producing more code doesn’t necessarily mean better software: AI-generated code often introduces errors that leave developers picking up the pieces. AI-generated code forces software developers to rework and debug the code that “only took a few seconds” to create. What’s missing and keeping AI from accurately producing and shipping code is a written, testable record of how the product should behave. Much of this context lives in disconnected tools or internal knowledge, leaving AI to guess at a developer’s intent. This is where test artifacts help AI-assisted development. Test context breaks down detailed user flows written in step by step detail. Unlike requirements or other dev artifacts that show a snapshot of how features were once built, tests capture your product’s truest expected behavior and your regression suite aggregates the cumulative and latest expected behavior of your product functionality including the multitude [...]

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What Happens to QA When AI Writes 100% of the Code?

Software Testing Magazine — Thu, 27 Aug 2026 15:39:30 +0000

Today, you can find tools that generate code and AI-assisted test automation tools that will handle the quality assurance part. Is it the death of traditional manual testing? In this article, Rimpal Mistry reminds us that human validation is still needed to provide the final check of delivered software. Author: Rimpal Mistry, Co-Founder & VP Operations @ Testscenario Over the past few weeks, we have been watching something interesting happen on some of our projects. Let’s take one specific project that has reached a stage where 100% of the code is being written by AI, with no direct human intervention in development. Features are being built by AI. Bugs are being investigated and fixed by AI. Code reviews are handled through automation. Deployments are automated too. From development to deployment, there is now very little direct human involvement. That part is impressive. But the more interesting part for us is what happened to QA. The requirement for manual testing did not go down. It actually grew. It Still Starts With a Requirement The process still starts normally. Someone needs a feature, change, or fix. Earlier, a developer would read the requirement, understand the codebase, build the feature, test it, fix issues, and send the change for review. Now much of that can go directly to an AI coding system. The AI reads the requirement, looks at the existing code, identifies what needs to change, and starts building. Humans still decide what needs to be built. But once that direction is [...]

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Confluence Alternative for Software Testing: 6 Docs Tools QA Teams Actually Use

Software Testing Magazine — Thu, 13 Aug 2026 12:50:22 +0000

Confluence can store QA docs, but it seldom helps testers find the right one when release pressure hits. The problem is rarely the editor. It is that test plans, environment runbooks, and release checklists drift out of date faster than anyone updates them, and a wiki that merely holds pages cannot tell you which ones still reflect reality. If you are looking for a Confluence alternative for software testing, this comparison grades six contenders on three weighted factors — QA tool-chain fit, AI-assisted freshness under human control, and real cost for a 20-editor team. How We Evaluated Confluence Alternatives for QA Teams We compared 20 documentation and test-management products against ten weighted criteria. Three carried the most weight: QA workflow fit (18 percent) — the tool must connect directly to Jira, GitHub, GitLab, CI/CD pipelines, and common test-automation tools. Freshness under human control (16 percent) — we scored agents and review cycles that detect drift, propose fixes, and wait for approval higher than raw text generation. Real team cost (9 percent) — all prices normalised to a 20-editor team, seats only. The remaining 57 percent covers permissions depth, authoring experience, migration tooling, AI controls, and security. For a broader market map first, see this guide to Confluence alternatives, then come back for the tester’s lens. The Six Best Tools at a Glance Rank Tool Best for Stand-out freshness feature Approx. cost for 20 editors* 1 Slite Keeping QA knowledge current Self-maintaining Slite Agent (detect → propose → approve) $400 [...]

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Cross-Browser Testing Tools (Free, Open Source, Paid)

Software Testing Magazine — Wed, 12 Aug 2026 14:00:17 +0000

When today’s applications run on various browsers (Chrome, Firefox, Safari, Edge, etc.) on different mobile or desktop devices with specific screen settings. This is why you need to perform cross-browser testing for your automated tests. This article lists the main desktop or online cross-browser testing tools available today. Some of these tools are open-source, some are commercial with a free plan. Use our contact form to make us aware of some cross browser testing tools that we should add to this list. Cross-browser testing is a software testing activity that check the quality of web applications across multiple browsers, devices and operating systems. Screen size, screen resolution, OS version, browser versions, JavaScript and CSS languages support are elements that impact how your users are viewing content on a moblie phone, a tablet or a desktop screen. Cross-browser testing helps you to understand and verify these different user experiences for the main devices and system used by your target audience. Here are some questions you should ask yourself when looking for a cross-browser testing tool: Are you testing on real devices vs. emulators/simulators? How many browsers, devices and operating systems are supported by the platform? How can you test: writing your own scripts, with a record & replay tool or supporting an existing software testing framework like Selenium? How much software testing power or which features do you need and get in the pricing plans: number of users, virtual location, testing time, parallel usage, support, external tool integration (bug tracking, continuous [...]

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