Expert Insights: Are You Overpaying for GUI Testing?

Testing tools and frameworks are often chosen with good intentions: they are familiar, flexible, or initially inexpensive. What is less visible is how testing costs accumulate over time, not just in licensing, but in engineering effort, maintenance, and opportunity cost.

This guide looks beyond upfront pricing to examine the real cost of GUI testing as systems grow and evolve. Drawing on first-hand insights from teams across multiple industries and platforms, it highlights the warning signs that testing effort is starting to outweigh its value, and offers a practical framework for deciding when a different approach is needed.

Introduction

For this guide, we interviewed Karim Boussema, Solutions Engineer at Qt Group, drawing on his first-hand experience across dozens of real-world development projects. His perspective reveals common GUI testing patterns, recurring pain points, and the moments when teams realize their current approach no longer scales. The result is a practical reality check for teams developing interfaces built with various technologies and frameworks, and a clearer view of when it’s time to rethink how GUI testing is done.

Meet Karim Boussema:

I have a background in R&D and support development and QA teams in adopting Squish for GUI test automation, Coco for code coverage, and Test Center for QA insights. I work on a wide range of projects across desktop, web, mobile, and embedded platforms. My focus is on helping teams establish practical, maintainable testing workflows for both Qt and non-Qt applications.

Karim Boussema, Solutions Engineer, Qt Group

The Hidden Cost of “Fine”

In countless conversations with QA leads, product owners, and developers, one phrase comes up again and again:

"Our current testing tool is fine."

But “fine” is deceptive. It’s the quiet acceptance of flakiness, the slow creep of maintenance overhead, and the silent frustration of test suites that break with every browser update or UI tweak. It’s the cost of doing things the way they’ve always been done, until something breaks in production, and suddenly “fine” becomes “how did we miss this?”

A critical factor rarely discussed openly is that quality assurance is often viewed as a cost center rather than a value driver. Even with open-source tools, testing teams are seen as an operational expense instead of a business enabler. This perspective misses the bigger picture.

Treating quality assurance as pure expense is like viewing smoke detectors as unnecessary overhead instead of recognizing them as early warning systems that prevent disasters, shares Karim.

Do You Treat QA as a Cost Center?

Let’s start with a simple analogy.

Imagine you buy your favorite yogurt. It’s tasty, affordable, and you trust the brand. But one day, you open it and find a bug inside. You’ll never buy it again.

That’s what happens when software ships with defects.

Customers don’t just file a ticket, they lose trust. And in industries like automotive or medical, a bug can mean a recall, a compliance violation, or a safety risk.

Reframing Quality Assurance as Risk Mitigation

Testing should not be treated as a cost center; it is an insurance policy against reputational damage. When approached correctly, it acts as an early warning system that catches issues before they reach users, and becomes a genuine competitive advantage.

The most effective arguments use concrete examples of what happens when quality fails. Imagine these situations that happen, but can be prevented:

Direct business impact

Imagine an automotive company that has recalled millions of vehicles due to software issues, costing billions in direct costs and reputation damage.

Customer lifetime impact

When customers encounter bugs in your product, they may never return. It's like buying yogurt that's cheaper and tastier than competitors but finding a bug in it one day means you'll never buy that brand again. The producer loses a customer for life, far exceeding any testing tool costs.

Early detection economics

Finding and fixing issues during development (shift-left testing) costs much less than production fixes, especially for embedded devices that might require expensive hardware recalls.

The Wake-Up Call: When “Fine” Isn’t Enough

So, when do teams make the switch?

Several situations consistently make organizations reconsider their testing approach.

Sometimes:

It's a new project that is taken as a chance to start fresh and do things right
It's a growing test suite that takes hours to run and fails unpredictably
It's a compliance audit that reveals gaps in traceability

Or sometimes it's just curiosity: a QA lead who takes a free demo and realizes there's a better way.

Six common triggers that lead teams to start looking at specialised GUI testing tools

Several situations consistently make organizations reconsider their testing approach, like system alerts that signal when your current architecture is reaching its breaking point:

Trigger #1: Test maintenance overtaking development

As projects mature, maintaining custom wrappers or open-source testing setups can consume as much time and budget as developing new features. Small UI changes often trigger a cascade of fixes across test utilities and scripts, creating continuous maintenance effort. When test upkeep regularly competes with development resources, it signals that the current testing approach no longer scales economically.

Trigger #2: Automated Dependency Updates

An often-overlooked trigger: browser updates that break existing automated tests. For example, Browser vendors (Chrome, Edge, Safari) release updates without advance notice, and everything breaks through your entire codebase.

Teams find themselves updating tools, scripts, and drivers to accommodate these changes while sprint deadlines loom unchanged. This maintenance work represents a hidden ongoing cost that eats up developer time quarter after quarter.

Trigger #3: Test Performance Problems at Scale

Test suites that ran fine when small become painfully slow as they grow. Teams realize their current tools can't handle larger workloads or have fundamental limitations when testing complex applications, like native apps with embedded web components.

Trigger #4: Starting a new project

Teams beginning fresh projects want the best setup possible. Without existing systems to worry about, they're more willing to try better tools rather than stick with familiar options that might hold them back.

Trigger #5: Growing project complexity

Current projects become too complex for existing testing methods. This typically involves supporting multiple platforms, requiring test coverage that manual testing can't provide, or growing beyond what current automation tools can handle.

When teams assign people to research market alternatives, it's usually because their current solutions can't keep up.

Trigger #6: Changing development phases

Teams moving from active development to maintenance phases need reliable automated regression testing. While manual testing worked during active development, maintenance phases require automated checks to ensure changes don't break existing functionality.

From Fragmented Effort to a Unified Modern Approach

For teams developing interface applications across frameworks and platforms such as Qt, Android, Windows, Java-based stacks, and HTML5/Web, particularly in embedded environments, the challenges can be even greater. Testing these technologies with generic tools usually requires workarounds and fragmented workflows. In many cases, teams must also accept that some aspects cannot be automated effectively. What is often missing is deeper support, stronger traceability, and the reliability needed to keep pace with evolving systems.

Automated and Native GUI Testing for Qt

Open-source Qt gives teams the freedom and flexibility to build powerful cross-platform applications. Many teams pair it with manual testing or open-source tools like Selenium, Appium, or custom wrappers.

These setups can work well until they hit limitations when it comes to deep Qt/QML introspection.

Instead of working around the UI, learn how to interact with it natively

Automated GUI Testing for Android-based UIs

Android powers a wide range of devices, from mobile phones and tablets to automotive and embedded systems. Many teams rely on UI automation frameworks or device-driven tests that struggle with fragmentation, performance, and long-term stability.

These approaches often break as UIs evolve or when hardware configurations change, making maintenance costly and slowing down release cycles.

Instead of relying on fragile UI interactions, learn how to test Android applications using native, object-level access

Automated GUI Testing for Windows

Windows applications span classic .NET, WPF, WinForms, and modern WinUI platforms. Teams often combine unit tests with UI automation tools that rely on screen coordinates or accessibility layers, which can be brittle and hard to scale.

As applications grow, these tests become difficult to maintain and may fail to detect UI regressions until late in the development cycle.

Learn how to build reliable Windows GUI tests by interacting with UI components directly

Automated GUI Testing for Java

JavaFX and Swing remain foundational in enterprise and legacy desktop applications. However, GUI testing is often limited to unit tests, leaving UI regressions undetected until late stages. Open-source tools like TestFX or JemmyFX exist but, in certain cases, may lack robustness or integration with modern CI/CD pipelines.

Instead of manual or fragile UI testing, learn how to build reliable automation using object-level access to UI components

Ready to explore your options?

Begin with an honest assessment of your current testing challenges, then evaluate solutions based on their ability to solve your specific problems rather than their price tags.

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