Mathew Allen

  Anyone who has managed a test automation suite for more than a few months knows what happens when a developer renames a button or restructures a form. A handful of tests go red, someone spends the afternoon tracing failures that turn out to be changed locators rather than actual bugs, and real testing work gets pushed aside. This happens constantly in teams running automated tests at scale, and it is the exact problem self-healing test automation is designed to fix. Instead of treating every UI change as a failure, self-healing frameworks use AI to detect what changed, locate the element through alternative means, and update the script automatically. Let’s learn this in detail: What is Self-Healing Test Automation? Self-healing test automation is a Gen AI-powered capability that allows test scripts to recover on their own when the application changes in ways that would normally break them. Rather than depending on a single rigid locator like an XPath or CSS selector, self-heali...

  Software testing was supposed to get easier with automation. Write the scripts once, run them continuously, ship faster. But ask any QA engineer how their week is going, and you’ll hear the same story that half their time is spent fixing scripts that broke because a button moved or a pop-up appeared. The solution built to solve the testing problem became a testing problem of its own. Generative AI is changing that. Not by making automation slightly better, but by rethinking who writes the tests, how they stay current, and what it actually takes to ship with confidence. Here is what it is, how it works, and why it matters. Let us learn more in detail: What is Generative AI in Software Testing Generative AI in software testing refers to the use of AI models to create, adapt, and maintain test cases based on user intent and application context. Instead of writing test scripts step by step, teams describe what needs to be validated. The system interprets that intent and convert...

  Your users can still experience dropped calls, failed transactions, and slow app responses even when network health checks pass. These issues typically surface in production, where traffic moves across real network devices , paths, and carrier boundaries. Standard testing often confirms that a connection can be established, but it does not show how that connection behaves under load, during handoffs, or across different routing paths. That is where gaps begin to appear. Connectivity testing addresses this by validating how services perform end-to-end under real network conditions before issues reach users. This article explains where connectivity gaps appear, why they are often missed, and how to test for them in practice. Where Connectivity Gaps Are Most Likely to Appear Inter-Carrier Handoffs A session that performs well inside one carrier can degrade when it transitions to another, as routing policies, congestion handling, and prioritization differ. Both networks may appe...

  Modern applications rarely fail in just one place. A login button may work, but the session token might not persist. A checkout page may render correctly, but a payment callback can still break the order flow. That is exactly where end-to-end testing matters. It validates whether the full user journey works from start to finish across the interfaces, services, and data handoffs that make up the product. What is End-to-End (E2E) Testing? End-to-end testing is a software testing approach that verifies a complete application workflow from beginning to end. In simple terms, it checks whether the system behaves correctly the way a real user would experience it, while also confirming that connected components and data flows work together as expected. That is what makes E2E testing broader than checking a single function, page, or service in isolation. A good E2E test does not just ask, “Did this screen load?” It asks, “Can a user sign up, receive a confirmation, log in, complete a...

  AI has been essential to testing for some time now. It helped teams write test cases faster, generate snippets, clean up documentation, and suggest automation steps. That was useful. It reduced friction. It saved time. All this time, AI was in the co-pilot seat. However, times are changing. Before we can get into AI’s role in the SDLC, consider how testing has changed over time. The first stage: traditional testing was fully human-driven The starting point for most QA teams was manual testing. In that model, testers executed test cases themselves by clicking through user flows, entering data, and verifying outcomes. Manual testing still matters today, especially for testing without a fixed script, usability checks , and scenarios where human judgment is essential. But as products grew more complex and release cycles became faster, manual-only testing became harder to scale. Traditional automation improved that situation, but only to a point. Teams could run repetitive checks much...

  QR codes are becoming indispensable in today’s digital landscape, seamlessly integrating into various applications. As their usage grows, software testers must master QR code testing to ensure functionality and reliability. However, effectively testing QR codes requires specific expertise, often challenging for newer testers to grasp. This tutorial will explore the fundamentals of QR code testing and its significance in modern software testing . We’ll cover common scenarios that demand QR code testing and share practical tips for executing these tests accurately. By the end of this tutorial, you’ll have a comprehensive understanding of why QR code testing is crucial and how to approach it for optimal results. Understanding QR Codes A QR code — Quick Response code — is a two-dimensional (2D) barcode designed to quickly access digital information through a smartphone or tablet’s camera. Visually, it appears as a square pattern of black-and-white pixels. Beyond basic alphanumer...

  Debugging a webpage on a desktop is easy. On an iPhone, it is a different story. There is no built-in Inspect Element button in mobile Safari like the one many developers are used to in desktop browsers. That is why teams often get stuck when a layout breaks on iOS, a tap target does not respond, or a script behaves differently on mobile Safari. The good news is that inspecting elements on an iPhone is absolutely possible. The most reliable method is Safari’s Web Inspector on a Mac, Apple’s official workflow for inspecting and debugging web content on iPhone. If you do not have a Mac, there are still workable alternatives for lightweight inspection and debugging, including browser-based tools and cloud testing platforms. Can You Inspect Element on iPhone? Yes, you can inspect elements on an iPhone. But not in the same direct way you would on a desktop browser. For full inspection of HTML, CSS, JavaScript, console activity, and network behavior on iPhone Safari, the standard ...

  Software teams often need to decide where to use manual testing and where automation makes more sense. Manual testing helps catch issues that depend on human judgment, such as usability gaps or unclear workflows. Automation testing is better suited for repeated validation, large test volumes, and ensuring consistency across builds. This is rarely an either-or choice. Most teams use both. The key is knowing what to test manually, what to automate, and when to shift between the two as the product evolves. This guide explains the differences, use cases, and how to balance both approaches effectively. Manual Testing vs Automation Testing: Key Differences What is Manual Testing? Manual testing is a testing approach where testers validate an application by executing test cases without the use of automation scripts or tools. The tester interacts directly with the application, following defined steps while also observing how the system behaves under different conditions. Manual tes...