The Ultimate Guide to Automated Testing & QA: Strategies, Tools, and Best Practices

A bug in production never comes at the right time. Often in the middle of a campaign or rush, sometimes right after a "minor" update, and almost always where you least expect it. The result: stressed teams, stalled operations, frustrated customers, and a damaged brand image.

This is where the issue of testing and software quality ceases to be theoretical. QA and automated testing are not just a necessary step before going live: they are concrete levers for delivering faster and better, and offering a smooth customer experience. All with less stress and more reliability.

However, it is important to know how to approach this strategic issue correctly. Tests are often perceived as time-consuming, technical, and difficult to maintain. If poorly equipped or poorly integrated, they become a constraint rather than a catalyst.

In this guide, we offer a pragmatic approach to automated testing and Quality Assurance. The goal: to help you structure an effective strategy and choose the right tools (including on the mobile), and avoid common mistakes that turn production into a lottery and undermine the user experience.

IT Director, QA Manager, Digital Manager, Product Owner, Project Manager, Developer... Here you will find practical tips to help you regain control over the quality of your applications. Avoid any hiccups in the running of your internal and external platforms.

The fundamentals: understanding the testing environment

The vocabulary used in testing can sometimes be confusing. Before discussing automation, it is crucial to understand the distinctions between different types of tests, particularly the major difference between functional validation tests and non-regression tests (NRT).

Functional validation tests vs. non-regression tests

Although complementary, these two types of testing serve distinct purposes in the software lifecycle.

The functional validation test

It generally occurs at the beginning of the cycle or during the development of new features.

• Objective: Verify that the developed product meets specifications and business requirements ("Does the functionality meet the expected use case?")
• Method: The tester simulates user scenarios (positive and negative) to validate each module. They are not concerned with the underlying code ("Black Box testing"), but rather with mechanical fluidity.
• Examples: Check that an "Add to cart" button correctly updates the total, or that a link redirects to the correct page.
• When to use it? When a new system is created, when integrating new modules, or to validate a specific User Story.

The non-regression test

Often referred to simply as the "Regression Test," it is the guardian of stability. 

• Objective: To ensure that a code change (addition of functionality, bug fix, technical update) has not broken something that was already working ("Did I break something while fixing/adding something else?"). 
• Method: Test scenarios that have already been validated in the past are re-run.
• The crucial importance: Regression is a step backward. It is one of the major risks associated with frequent updates. TNR secures what already exists.

Should everything be automated?

The answer is nuanced.

• Functional Validation: Often manual at the outset, as the functionality is unstable and still being defined.
• Non-Regression: This is the ideal candidate for automation. Test cases are stable, repetitive, and tedious to execute manually with each release. Automation saves a tremendous amount of time and increases reliability.

What are the main types of automated testing?

A modern application relies on a complex architecture where everything is interconnected. To guarantee quality, it is not enough to check an interface on the surface. You have to make sure that the entire technical and business chain is sound.

Here are the main types of tests you need to cover your risks:

End-to-End (E2E) testing

This is the test that validates the real experience by verifying that all system components (front end, back end, database, third-party services) work together seamlessly. The bot behaves exactly like a user: it navigates the interface, fills out forms, and validates key steps. To maximize its effectiveness, it is automated primarily on critical paths that generate revenue.

For example, a typical scenario will simulate a complete purchase funnel, from product search to order confirmation page. The preferred approach today is to use no-code solutions, which allow these functional paths to be modeled quickly without technical complexity.

API testing

Even before having a graphical interface, your applications communicate with each other via APIs. This type of test aims to validate this part, without depending on the slowness or visual changes of the interface.

In concrete terms, technical requests are sent to the server (for example, a request to create an account) and the response is checked to ensure that it contains the correct information (user ID). This test should be automated early in the development cycle or to secure exchanges between two software programs. The approach is purely technical.

Graphics tests

A feature may work technically (when the code is good), but be unusable by the customer due to a display bug. The goal here is to detect visual regressions that a conventional functional script cannot see, such as a "Pay" button that ends up hidden under the footer after a CSS update, or text that overlaps an image.

These tests must be automated systematically when updating the user interface (UI) or Design System. They are based on a "Pixel Perfect" comparison approach: the tool compares the current screen with a previously validated reference screenshot and alerts you to any visible discrepancies.

Performance and load testing

Your site works well with 10 users, but will it hold up on D-day ? The goal is to identify your infrastructure's breaking point and slowdowns before they impact real customers. A classic scenario involves simulating the sudden arrival of 50,000 simultaneous visitors to prepare for sales or the airing of a TV commercial.

These tests are automated on an ad hoc basis, prior to major commercial events or before a major overhaul of the server architecture. The technical approach uses load injectors that create thousands of virtual users bombarding the site with requests to measure the response of the servers under pressure.

Accessibility testing

Digital inclusion is a legal and ethical obligation to ensure that 15 to 20% of the population is not excluded. This testing aims to ensure that the site is usable by people with disabilities (visual impairment, keyboard navigation, etc.). For example, we will check that all images have a descriptive "Alt" tag, that color contrasts are sufficient, and that forms are correctly labeled.

The ideal solution is toautomate these accessibility checks on an ongoing basis to prevent the integration of new content from lowering the site's compliance rating. This is done through automated scans that analyze HTML/CSS code to identify deviations from current standards.

Data Layer & Analytics Testing

Often overlooked by technical teams, Data Layer tests are often overlooked by technical teams, yet they are vital for marketing. Their purpose is to ensure the reliability of data collection: if your data is incorrect, your business decisions will be too. For example, we ensure that the "Order Confirmation" event correctly reports the exact amount and currency in Google Analytics or your CRM.

It is recommended to automate these checks each time the tagging plan is modified or new commercial pages are published online. The automation tool works by "listening" to outgoing network requests during browsing to verify that the correct tags are triggered with the expected values.

When and why should you automate your tests?

Automation is not an end in itself; it is an investment that must be profitable. We don't automate everything; we automate what is valuable to the business and technical teams.

Why automate?

Securing revenue on an e-commerce site is a priority. A two-hour outage of the shopping cart or payment tunnel can cost thousands of euros. Automation acts as insurance that monitors your critical processes 24/7, alerting you immediately in the event of a malfunction.

Automating testing speeds up production releases. In an agile environment where speed is key, waiting three days for a team to manually validate a version is no longer acceptable. Automation reduces this acceptance time to a few hours or even minutes, enabling more frequent deployments.

When performing repetitive tasks, human attention quickly wanes, leading to errors. An automated system never tires: it will execute the same scenario the 100th time as it did the first, ensuring consistent reliability.

When should you take the plunge?

When your teams spend more time checking that existing systems are working (TNR) than testing new features. This is the most common warning sign: the technical debt of manual testing slows down innovation.

You want to switch from monthly production to weekly or daily production because release cycles are getting shorter. Without automation, maintaining this pace without sacrificing quality is impossible.

Finally, when the number of possible routes explodes (mobile, desktop, tablets, multiple browsers). The test matrix exceeds human capacity: it becomes physically impossible to check everything manually before each update.

How to successfully automate your functional tests?

Automation cannot be improvised. To transform your QA processes into a growth driver, you need to follow a rigorous methodology.

Why automate? The concrete benefits

1. Save time and money: Robots perform tests much faster than humans and can run 24/7, freeing up your teams for higher value-added tasks.
   
   
2. Reliability: Automation eliminates human error (inattention, fatigue) in repetitive tasks.
   
   
3. Accelerated time-to-market: Faster testing campaigns mean more frequent releases (continuous delivery).
   
   
4. Extended test coverage: It becomes possible to test thousands of combinations of data or configurations (browsers, operating systems) that would be impossible to cover manually.

The 7 key steps to successful automation

1. Plan the process : Define the scope. What is critical for the business? Don't try to automate 100% of the application right away. Focus on critical paths.
   
   
2. Choosing the right tool: This is a strategic decision. The tool must be suited to your team's skills. No-code solutions (such as Mr Suricate) are now widely used because they allow business users (non-developers) to create and maintain tests. Even technical users find them advantageous because, in addition to the speed with which test scenarios can be created, they also facilitate their maintenance.
   
   
3. Design the framework: Define your standards. Will you use a keyword-driven or data-driven testing approach? A good initial structure facilitates future maintenance.
   
   
4. Prepare the test environment: Ensure you have stable test data (datasets) and an environment (Pre-production, Staging) that is identical to production to avoid false positives.
   
   
5. Writing scripts: Or recording them via no-code interfaces. This is the scenario creation phase. Developing a comprehensive and precise test plan facilitates this step, in addition to precisely defining the scope to be covered.
   
   
6. Run the tests: The simplest step once everything is in place. Ideally, integrate it into your CI/CD pipeline. Practical automation solutions generally allow you to configure executions (campaigns, sequences, recurrence, etc.).
   
   
7. Analyze and Maintain: A test that fails must be analyzed immediately. Is it a real bug or an obsolete script? Test maintenance is the key to sustainability.

How to implement an effective QA strategy?

There is no universal magic formula. A good quality assurance strategy must be tailored to the size of your company, your business challenges, and the maturity of your teams. Here's how to approach it based on your context.

Start-ups and scale-ups

Here, resources are limited and the product is constantly evolving. The goal is not to cover everything, but to avoid blocking bugs without slowing down development. The strategy is to automate only the critical paths (registration, adding to cart, payment). We secure the business while maintaining a high degree of agility for the rest.

SMEs and mid-sized companies

At this stage, the challenge is to make existing processes more reliable while continuing to deliver new features. The QA strategy must become systematic: each release must be preceded by an automated regression testing campaign. This is often when test tools are connected to project management tools (Jira, Trello) to streamline collaboration between business and technical teams.

Key Accounts and CIOs

With complex ecosystems combining modern technologies and legacy systems, QA is becoming a governance issue. Testing must be industrialized on a large scale and integrated into continuous integration (CI) and continuous deployment (CD) pipelines.CI/CDpipelines. The goal is to maintain a consistent level of quality across dozens of different applications, involving both developers and business analysts.

Common mistakes in QA automation

Here are the strategic mistakes we see most often when companies embark on automation without knowing the classic pitfalls.

Wanting to automate 100% of tests

This is the most persistent myth. Automation takes time (creation and maintenance). Trying to automate an exotic test that is only used once a year or a purely visual and subjective feature is counterproductive.

• Best practice: Focus on the 20% of tests that cover 80% of business risks. Let humans handle complex, rare cases or those that require subjective judgment.

Automating unstable features

Trying to create an automated test on a page that changes its design every other day is a waste of time. Your script will break with every update.

• Best practice: Wait until the feature is stable (or "frozen") before automating it. During active development, manual testing remains more agile.

Neglecting script maintenance

It is often thought that automation is a "one-shot" process: you create the test and then forget about it. This is incorrect. The application evolves, and the tests must evolve with it. If you do not set aside time to update your scripts, they will eventually all fail (false positives), and the team will lose confidence in the tool.

• Best practice: Treat your tests as living code. Always set aside time in your sprints to maintain the existing test suite.

Which automated testing tools should you choose?

The market for testing tools is vast and can seem intimidating. To make the right choice, the main criterion is not only technological, but human: who will create and maintain the tests on a daily basis? There are generally three main families of tools.

Code-based solutions

This is the traditional approach, represented by frameworks such as Selenium, Cypress, or Playwright.

• Who is it for? Experienced developers and QA engineers.
• Advantages: Total flexibility and free licenses (Open Source).
• Disadvantages: They are very time-consuming. Creating and maintaining scripts requires solid development skills. In addition, scripts are often fragile and break at the slightest technical change to the interface, increasing technical debt.

Low-code solutions

Low-code low-code tools attempt to simplify test writing by reducing the amount of code required, while retaining programming logic.

• Who is it for? Intermediate technical profiles.
• The principle: A compromise between pure code and visual interface. Although faster than pure code, these tools still require a certain level of technical proficiency and sometimes struggle to be adopted by purely business-oriented teams.

No-Code Solutions (SaaS)

This is the modern approach that is widely acclaimed for its speed and accessibility (this is the positioning of solutions such as Mr Suricate).

• Who is it for? Everyone: QA Managers, Product Owners, business teams, and even developers who want to save time.
• The principle: Tests are created by recording a user journey or assembling pre-designed visual building blocks. No coding is required.
• Key benefits: Tests can be created in minutes rather than hours. Maintenance is often facilitated by intelligent algorithms that recognize elements even if they change slightly. This democratizes quality: those who know the business rules best are the ones who validate the product.

Mobile focus: choosing the right tool for your applications

The testing mobile applications is a much more complex challenge than traditional web testing. Why? Because of fragmentation.

The complexity of the mobile world

Unlike the web, where a few browsers dominate, mobile devices require juggling between: 

• Two major operating systems : iOS and Android, with very different behaviors.
• A multitude of OS versions: Not all of your users have the latest version of Android or iOS.
• Hardware: Screen sizes , resolutions, processor power, memory (RAM).
• Network conditions: 4G, 5G, unstable Wi-Fi, airplane mode, etc.

Criteria for choosing a mobile testing tool

To ensure user loyalty (users uninstall buggy apps in seconds), your testing tool must tick several boxes: 

1. Cross-Platform & Device Farm Support: It is impossible to purchase every phone on the market. Your tool must connect to services such as BrowserStack or offer its own farm of real devices for remote testing on actual devices.
   
   
2. Accessibility (No-Code): Mobile development is technical, but testing doesn't have to be. A tool that allows scenarios to be recorded without coding democratizes testing within the team.
   
   
3. CI/CD integrations: The tool must interface with your management tools (Jira, Trello) and your deployment pipelines (Jenkins, GitLab, etc.).
   
   
4. Complete bug reports: In the event of a crash, the tool must provide not only the "error," but also the context: screenshot, video of the session, system logs, battery and network status at the time of the crash.

Securing production: mistakes to avoid

The production launch (MEP) is the moment of truth. It is also the moment when stress is at its peak. Even with good testing, strategic errors can ruin everything.

Common technical errors

• Performance and Load: An application that works for 10 testers may crash with 10,000 simultaneous users. Don't neglect load testing.
  
  
• Logical errors (semantics): The code does not crash, but the result is incorrect (e.g., a 20% discount that applies €20). Only rigorous functional business tests can detect these errors.
  
  
• Integration Issues: Often , module A works, module B works, but A+B crashes. End-to-end testing is vital here.
  
  
• Security: Authentication or data access vulnerabilities . An error that can be very costly in terms of reputation and fines (GDPR).
  
  
• Compatibility: The famous "it works on my machine." Don't forget cross-browser testing (Chrome, Safari, Firefox, Edge).

MEP Strategy Errors

Beyond the code, it is often the process that is flawed: 

• No soft launch (beta testing): Launching "Big Bang" for everyone is risky. Open your service to 5% of users first to "iron out" the last bugs.
  
  
• Post-launch blindness: MEP is not the end, it's the beginning. Performance must be monitored immediately after launch.
  
  
• Not deploying often enough: It's counterintuitive, but the longer you wait between deployments, the higher the risk of errors (too many changes at once). Frequent, small (atomic) MEPs are safer and easier to debug.

Conclusion: Towards intelligent and accessible QA

The era of tedious, manual testing is coming to an end. To remain competitive, companies must embrace automation, not to replace humans, but to allow them to focus on the quality of the user experience.

Whether for web or mobile applications, the key lies in choosing the right tools. Modern, no-code-based solutions now make it possible to break down the silos between developers and business teams, ensuring that software quality is everyone's business.

Mr Suricate of this approach, offering a codeless solution "Made in France" that can detect bugs before and after deployment, covering all your web and mobile user journeys.

Ready to take it to the next level? Automation is waiting for you.

Check out our FAQ dedicated to QA testing

Should everything be automated?

No, and it's a common mistake to try to do so. The goal is not to achieve 100% coverage, but to cover 100% of critical risks. Exploratory testing, usability analysis, and new features that are still unstable are best tested manually by humans.

What ROI can you expect from automated testing?

Return on investment is measured in three specific areas:

1. Time savings: Your teams no longer spend entire days performing repetitive manual tasks.
2. Risk reduction: How much does an hour of downtime on your shopping cart cost you? By preventing critical bugs in production, the tool often pays for itself as soon as the first anomaly is detected.
3. Acceleration: You can deploy faster and more often, which is a direct competitive advantage.

How long does it take to implement a QA strategy?

It depends greatly on the approach chosen. With traditional code-based methods (internally developed frameworks), it often takes several months to achieve a stable and reliable test suite. With a no-code approach, it is possible to achieve a stable and reliable test suite in a matter of days. No-Code (SaaS) approach, the time frame is drastically reduced: the first critical scenarios can be operational in a matter of days, delivering value from the very first week.

What happens if my interface changes frequently?

This is the number one fear: having to rewrite all tests at the slightest change to the site. With older scripts (such as Selenium), this was the case. Today, modern tools use intelligent selectors and AI. If a button changes color or shifts a few pixels, the tool still "recognizes" it and the test continues to run. This drastically reduces maintenance.

Automated testing or manual testing?

They should not be seen as opposites; they are complementary. Automation is there to handle volume, repetition, and tedious tasks (checking 500 times that the login works). Humans, on the other hand, bring their intelligence, creativity, and ability to judge "experience" and feelings, which a robot cannot do. A good QA strategy uses automation to free up human brainpower.

Should we test on emulators or real phones?

For pure development, an emulator is sufficient. But for final validation (QA), it is imperative to test on real devices. An emulator will never accurately reproduce battery overheating, network interruptions (4G/Wi-Fi switching), or the specific touchscreen features of a particular model. To ensure that no customer will be blocked, nothing beats testing on a real device.

Who should write the tests?

Historically, this task was reserved for developers or technical QA engineers. Today, the underlying trend is to bring testing closer to the "business." Thanks to no-code tools, it is now Product Owners (POs), Business Analysts, or functional teams who create the scenarios. This makes more sense: they are the ones who best understand the business rules and the behavior expected by the end user.

Does automation slow down deployment?

On the contrary, it is designed to speed it up. By integrating automated testing directly into your deployment pipelines (CI/CD), verification is performed instantly each time developers push new code. If it's green, it goes into production. If it's red, it's blocked. This eliminates the bottleneck of manual acceptance testing, which used to take several days.