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Technology is an indispensable part of our daily lives, permeating nearly every domain imaginable - from banking to fitness, and shopping - mobile and web apps exist for everything.
Every great digital product - whether it’s a mobile app, a web platform, or an IoT solution - shares one common trait: it works seamlessly for its users. Behind the scenes, that reliability is ensured through Quality Assurance (QA) testing.
QA testing is the process of evaluating a product to make sure it functions as intended, is easy to use, and is free of critical bugs before it reaches users. It’s not just about finding mistakes - it’s about building trust. A smooth, error-free experience protects your brand’s reputation, prevents costly downtime, and creates loyal customers who come back again and again.
In today’s fast-moving development world, skipping QA isn’t an option. With AI-driven tools, automated testing, and more collaborative workflows, QA in 2025 has become faster, smarter, and more effective than ever.
In this guide, we’ll walk you through everything you need to know to successfully QA your app - from the fundamentals of planning and testing, to the latest AI-powered tools and emerging best practices - so you can deliver products that your users will truly love.
A good QA process doesn’t happen by accident - it’s structured and intentional. Breaking it into stages helps teams stay organized, cover all the important details, and make sure nothing slips through the cracks. At Yeti, we approach QA in three key phases: Planning, Testing, and Reporting.
This is the blueprint stage. The project management team works with design and development to decide:
A big part of planning is writing test cases. Think of a test case as a recipe. It’s a set of step-by-step instructions for checking whether a feature works as intended. For example:
Test cases mimic real-world use, so the QA team isn’t just checking if the code runs - they’re validating that the product behaves in a way that makes sense for actual users.
In 2025, AI tools, like TestRail AI and QA Touch, can speed up the QA process by auto-generating test cases from user stories, acceptance criteria, or even design mockups. This saves time and ensures coverage of scenarios that humans might overlook.
Once test cases are ready, the QA team begins testing the product. This can involve:
Manual testing
Testers follow test cases step by step, just like a real user would. Manual testers might focus on the “feel” of the app - does it make sense, is it intuitive, does anything look broken?
Automated testing
Scripts run tests automatically to quickly check repetitive tasks. Automated testing might focus more time consuming tasks, like testing every possible combination of inputs in a form,
Exploratory testing
Instead of following a script, testers (or AI tools) freely “explore” the app, clicking through different flows and trying unexpected inputs. This helps uncover edge cases or issues that might not be captured in planned test cases.
AI-powered tools, like Mabl are able to perform exploratory testing automatically. These tools learn from user flows and “wander” through the app to surface edge cases developers might not have thought of.
When issues are found, they’re logged into a project management tool (at Yeti we use ClickUp). Each report includes:
AI can now auto-triage bug reports - clustering duplicates, suggesting likely root causes, and even prioritizing issues based on severity.
Before diving into the different types of testing, it’s worth remembering that QA is inherently a team effort. It’s not just a final box to check at the end of development - it works best when design, development, project management, and QA all collaborate from the start.
Each team brings a unique perspective, and when those viewpoints come together, you catch issues earlier, prevent misunderstandings, and make sure nothing important slips through the cracks.
For example:
Without this kind of collaboration, bugs may be caught too late, requirements may be misunderstood, or fixes may cause delays. Working together early and consistently helps prevent costly rework and ensures a smoother launch.
Here are some tips for ensuring your QA testing process runs smoothly across teams:
Not all testing is created equal - sometimes you need a full sweep of the entire system, and other times a quick check-up is enough. The right approach depends on where you are in the development cycle and what changes have been made. Here are the two most common testing approaches teams use to keep products running smoothly.
Usually done at milestones, like major releases and client handoff, this is a “deep clean”, checks the entire system, ensuring:
This is like a “spot check.” After a small update or bug fix, testers verify that nothing else broke in the process. Because software is so interconnected,changing one line of code can unintentionally affect something else, making regression testing critical.
Tools like Applitools use AI to automatically detect tiny visual inconsistencies across devices - like a button that is slightly misaligned on Android but fine on iOS.
Testing an app isn’t one-size-fits-all - the experience of using a website in a browser is very different from using a mobile app on a phone. That means the QA process has to adapt, too. From browser quirks to touch gestures, each platform brings its own unique challenges and opportunities for bugs to hide. Here’s what to look out for when testing across web and mobile.
Environment:
Web apps need to be tested across different browsers (Chrome, Safari, Edge, and sometimes Firefox) because each browser can interpret code slightly differently. For example, a button might look perfect in Chrome but appear misaligned in Safari. It’s also important to check on both desktop and mobile browsers since layouts often shift on smaller screens.
Experience:
Web apps must adapt to a wide range of screen sizes and devices, from large monitors to tablets and smartphones. QA testers often use responsive design testing tools (like Chrome DevTools or BrowserStack) to simulate different resolutions and devices. Common checks include:
Many QA teams now use cloud-based device farms (like AWS Device Farm or BrowserStack App Live) to instantly test across hundreds of real devices without needing to physically own them. AI tools can even flag inconsistencies - like if a button is too small to tap on a certain screen size - helping ensure apps are accessible and user-friendly on every device.
Building for mobile means building for two very different worlds. While iOS and Android apps often share the same core features, the way they’re tested can vary dramatically. Differences in devices, operating systems, design guidelines, and even app store approval processes mean QA teams can’t take a one-size-fits-all approach. Understanding these distinctions is key to ensuring your app feels polished, reliable, and native no matter which platform your users prefer.
When it comes to mobile QA, iOS and Android bring very different challenges. iOS offers consistency, while Android brings variety = and each requires a different testing mindset.
Apple makes both the hardware (iPhone, iPad) and the operating system, which creates a relatively consistent testing environment. With fewer screen sizes and device variations to worry about, iOS testing is usually simpler than Android. Still, it’s not completely challenge-free.
Key iOS QA challenges include:
Android devices are produced by many manufacturers (Samsung, Google, OnePlus, Motorola, and more), creating a much more fragmented environment. QA teams need to confirm the app works across budget devices and flagship phones alike.
Key Android QA challenges include:
In 2025, many teams address Android’s complexity with cloud-based device farms (like BrowserStack or AWS Device Farm), which provide instant access to a wide range of real devices. Paired with AI-powered visual testing, these tools can quickly highlight layout or performance issues without requiring manual checks on every phone.
An app that works perfectly on one version of an operating system might behave very differently on another. That’s why QA doesn’t just test across devices—it also has to account for operating system (OS) versions.
Apple users tend to upgrade quickly, which makes testing simpler. Most QA teams focus on the latest iOS release and sometimes one version back, since those two cover the majority of active devices.
Android is much more fragmented. Because device manufacturers (Samsung, Motorola, etc.) control update schedules, many users stay on older versions for years.
Some AI-powered QA tools can now automatically flag which OS versions are most likely to cause compatibility issues based on crash logs and historical data. This helps teams prioritize testing efforts where they’ll have the most impact.
Beyond just functionality, each platform has its own look and feel. Apple and Google publish design guidelines that shape how apps are expected to behave. QA isn’t just about checking whether buttons work - it’s about ensuring the app feels natural to users on each platform.
Apple’s Human Interface Guidelines emphasize simplicity and consistency. Navigation bars, icons, typography, and gestures (like swipe-to-go-back) are expected to behave in very specific ways. If an iOS app breaks these conventions, for example by placing primary navigation at the top rather than the bottom, at the bottom, users might feel confused.
Google’s Material Design Guidelines encourage flexibility and customization. Android apps often have different navigation patterns (like the hamburger menu or bottom navigation), varied layouts, and system-level back buttons or gestures.
QA testers need to verify that apps not only work, but also feel native to each platform. An iOS app that looks or behaves like an Android app (or vice versa) can feel “off” to users, leading to frustration, bad reviews, or even App Store rejection.
In 2025, AI-powered visual testing tools (like Applitools or Percy) can now compare your app’s interface against Apple’s and Google’s guidelines automatically, flagging deviations that might confuse users or cause compliance issues.
Even if your app passes all internal QA checks, it still has to clear the app store review process before reaching users. Both Apple and Google require apps to meet specific standards, and a failed review can delay your launch by days - or even weeks. That’s why QA isn’t just about catching bugs; it’s also about ensuring compliance with each store’s rules.
Apple App Store
Apple is strict. Every app update must go through a review process that checks for crashes, guideline compliance, and performance. This can take 24–48 hours or more. If QA misses something, it could delay the release. Here are the Apple Stores iOS App Requirements
Google Play Store:
Google’s review process is usually faster and more flexible. However, it has tightened in recent years, especially around privacy and security. Here are the Play Store’s Android App Requirements
AI tools can now run pre-submission compliance checks against both Apple and Google’s guidelines, catching common reasons apps get rejected (like missing permission disclosures).
Before an app reaches the public app stores, it needs to be tested in a safe, controlled environment. Both Apple and Google provide built-in tools that let QA teams and clients try out pre-release versions without making them publicly available.
On iOS, QA teams typically use TestFlight, Apple’s official pre-release testing platform. It allows developers to:
This makes TestFlight essential for catching bugs and gathering feedback before wider release.
For Android, Google Play offers Internal Testing tracks. These allow developers to:
In 2025, both Apple and Google have improved their pre-release tools with automated crash reporting and analytics. Some AI testing platforms can now integrate directly with TestFlight or Play Console, automatically logging issues and even suggesting fixes before the app goes wider.
The world of QA is evolving quickly. With the rise of AI, automation, and distributed teams, testing today looks very different than it did even a few years ago. Here are some of the most important trends shaping QA in 2025:
Modern QA tools now use AI to generate and maintain test scripts automatically. Instead of a tester manually writing out every step for every feature, AI can scan design files, user stories, or past bug reports and create tests on its own. This reduces repetitive work, helps teams cover more scenarios, and keeps tests up to date as the product evolves.
For example, if a new “checkout” flow is added to an e-commerce app, an AI tool might automatically build test cases for entering credit card details, handling errors, and confirming successful purchases.
Traditional automated tests often “break” when something changes, even if the app still works fine. For example, if a button label changes from “Submit” to “Send”, old tests might fail.
Self-healing tests use AI to recognize these small changes and adjust automatically without human intervention. This makes automated testing much more resilient, cutting down on maintenance time and false alarms.
In the past, QA happened at the end of development - basically as a final check before launch. Today, teams are “shifting left,” meaning QA is integrated earlier, even at the design and requirements phase. This is important because, the earlier a problem is caught, the cheaper and easier it is to fix. Shift-left testing prevents small issues from becoming big, costly ones later.
Instead of testing only in-house, companies now recruit real users from around the world to test pre-release versions of apps. This ensures coverage across a wide variety of devices, networks, and cultural contexts, and gives a more accurate picture of how products behave “in the wild” with real users.
Example: A ridesharing app might be tested by people in cities with weak mobile networks to see how it performs under poor connectivity.
Making products usable for everyone - including people with disabilities—is both a legal requirement and good business practice. Accessibility testing checks compliance with WCAG (Web Content Accessibility Guidelines).
AI-powered tools now automatically scan apps for issues like low color contrast, missing alt text, or buttons that are too small to tap. Some even simulate color blindness or screen-reader interactions.
Want to learn more about accessibility in software development? Here’s our free ADA compliance guide and checklist!
Quality Assurance is more than just “catching bugs.” It’s a holistic process that ensures your product delivers value, builds trust, and strengthens your reputation. In 2025, with AI-driven tools and smarter workflows, QA has become more proactive, predictive, and collaborative than ever before.
Whether you’re launching a new feature or preparing for a major release, a strong QA process is your safeguard against costly mistakes - and your ticket to delighted users.
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