Complete Guide to Automated Functional Testing

Embark on a journey through the intricacies of automated functional testing. This guide highlights challenges, strategies, and essential tools, emphasizing the synergy between functional and automated testing. Step in and enhance your functional testing endeavors.

By Federico Toledo and Matías Fornara

In this guide, we’ll delve deep into the who, what, where, when, why, and how of functional test automation. You’ll uncover both the IT and business benefits of test automation and gain insights into the right moments to opt for automation. Plus, we’ll impart some top-tier practices and strategies to ensure your efforts yield optimal results.

By the time you finish reading, you’ll be poised to present a robust plan for functional test automation to your team and kickstart its execution.

What is Automated Functional Testing?

If you take the traditional definition of automation from industrial automation, you can say it refers to a technology that can automate manual processes, bringing about several other advantages:

  • Improvement in quality, as there are fewer human errors.
  • Improvement in production performance, given that more work can be achieved with the same amount of people, at a higher speed and larger scale.

This definition also applies perfectly to automated functional testing (or checking).

Why Automating Functional Testing?

Functional testing primarily focuses on the software’s behavior according to its requirements, while automated testing emphasizes the methodologies, tools, and scripts used to execute these tests automatically.

Now, we would like to bring the “Zero Accumulation” theory forward. Basically, the features keep growing as time goes on (from one version to the next) but the tests do not grow. In fact, we haven’t heard of any company that hires more testers as it develops more functionalities.

As a product grows, you have to choose what to test and what not to test, leaving many things untested. 

test automation excuse diagram

Test executions are not cumulative. Every time a new version of the system is released it’s necessary (well it’s desirable, yet should be necessary) to test all the accumulated functionalities, not just the ones from the last addition. This is because it’s possible that some of the functionalities implemented in previous versions change their desired behavior due to the new changes. 

The good news is that automation is cumulative. It’s the only way to make testing constant. The challenge is to perform testing efficiently, in a way that pays off.

test effort vs product versions graph

When people say they’re doing automated functional testing, they are using an automated functional testing tool to automatically check that the software functions as expected. It’s a blend of both worlds – ensuring functionality while saving time and effort.

Teams leverage test automation tools to optimize the functional testing process, for both mobile and web applications. By incorporating continuous testing into the mix, there’s a seamless flow in test management. This approach enhances test coverage, ensuring that all functional tests are thorough and reflective of user needs, resulting in more reliable software products.

Building on these tools and processes in the software realm, automation testing has become paramount in ensuring applications function correctly across all browsers and platforms, thanks to cross-browser testing.

Specifically, functional tests are geared towards validating if a software function operates in line with the defined specifications. With a broad array of automation tools and testing tools available in the market, businesses can now choose tools that best fit their requirements and optimize their testing process.

These tools not only guarantee accuracy but also expedite the testing cycle, allowing for swifter and more efficient software delivery. In this light, automated functional test firmly cements its place as a cornerstone in the evolving landscape of software testing.

What is the Difference Between Functional Testing and Automated Testing?

First and foremost, we need to know these crucial differences. While functional testing (or manual testing) and automated testing serve different purposes in the software development cycle, they both aim to ensure the production of high-quality software. As automation becomes increasingly prevalent, distinguishing between these two testing approaches is crucial.

Dive into this article to learn more about functional testing vs. automated testing.

Which Types of Tests Can Be Automated?

As we are focusing on automated functional testing in this guide, we have to discuss regression tests. Although it’s one of the most popular types of tests to automate, it’s not the only use for test automation.

Take a look at this article to know all the types of tests that can be automated!

Regression Testing

Regression tests are a subset of scheduled tests chosen to be executed periodically, for instance, before a product release. Their aim is to verify that the product hasn’t suffered any regressions.

Regression testing is the process of testing software applications to ensure that recent changes in code, such as new features or bug fixes, have not adversely affected existing features. Its primary goal is to catch unintended side effects that might arise after modifying the software.

Regression testing can be done manually or using automated tools, and it is an essential part of the software development lifecycle to maintain software quality. Whenever a change is made to the software, regression tests are run to ensure that the rest of the system remains intact and functions as expected.

Regression Testing in Agile

Regression testing in Agile ensures that recent code changes haven’t adversely affected existing functionalities. As features are continuously added or modified in Agile sprints, regression tests are frequently run to catch any unintended side effects, ensuring that the software remains robust throughout its iterative development.

Automated testing tools are often used to efficiently manage and execute these tests due to the recurring nature of Agile cycles. We invite you to read this article about the role of regression testing in Agile.

Benefits of Automated Functional Testing

Embarking on the journey of automated functional testing offers more than just bug detection. While many consider the discovery of errors as the prime metric, the advantages begin unfolding from the very initiation of test modeling and specification. Plus, it’s essential to remember that the insights derived from test results are equally invaluable.

  • Immediate Benefits from Test Modeling: Contrary to the belief that the primary benefit is realized only when an error is identified, the rewards actually emerge the moment you initiate the process of formalizing the tests.
  • Verification Beyond Error Detection: Discovering an error isn’t the sole merit. Verifying that the tests are scrutinizing the right parameters and ensuring they function as they should is equally vital. As highlighted by an article in Methods and Tools, automation often uncovers a significant number of bugs.
  • Rigorous Testing During Automation: The process of automation requires diving deep into functionalities, experimenting with varied data, and more. Often, this means that while you’re trying to automate, you’re also inadvertently executing rigorous testing.
  • Beware the Pesticide Paradox: If you’ve automated tests for one module and believe that’s sufficient, do you halt further testing? This presents a risk: the automated tests might not encompass all functionalities, mirroring the pesticide paradox.
  • Quality Over Quantity: It’s a misconception that a vast number of tests equate to comprehensive testing. You might have thousands of tests, but if they aren’t thorough, if they’re too similar, or if they bypass critical functionalities, they’re not as effective as you think.
  • True Value of Automation: It’s not about the sheer number of tests or their frequency, but about the actionable insights they yield.

Learn more about the benefits of automated functional testing.

What Percentage of Functional Tests Should be Automated?

From our experience, it’s safe to say that there is a high ROI in test automation. We’ve seen that the cost of a single defect in most organizations can offset the price of one or more tool licenses. Also, coding defects found post-release can cost up to 5x more to fix than those found during unit testing.

While there isn’t a one-size-fits-all percentage for how much functional testing should be automated, the decision depends on the ROI and the repetitiveness of tests.

Automation offers substantial benefits, including the high ROI where the cost of post-release defects can outweigh tool licensing costs. It brings value in improving software quality, reducing operational issues, and decreasing bug-fixing costs. Modern tools, like and mabl, enable even non-coders to automate tests efficiently.

However, the key is to automate tests that are frequently executed and to weigh the cost of automation against the anticipated number of test executions. If a test case will be run multiple times across various versions and platforms, it’s often more cost-effective to automate.

Note that the cost of a single repetition is greater in the automated case. The graph below represents this hypothetically. Where the lines cross is the inflection point at which one makes more sense cost-wise than the other. If the test case is executed less than that number of times, it’s better not to automate. Conversely, if you are going to test more than that number, then it’s better to automate. 

cost vs repetitions graph

Read more about what percentage of functional tests should be automated and go into an in-depth breakdown of the math behind the potential ROI of test automation.

Types of Automated Functional Tests

Automated functional tests can be a game-changer in agile environments, ensuring a faster and more efficient development process.

The Agile Test Automation Pyramid, introduced by Mike Cohn, emphasizes the importance of a strong foundation with unit testing, which tests individual ‘units’ of software like functions or methods.

There are various methods to automate unit testing: the Test-First approach linked with Test-Driven Development (TDD), the traditional Test-Last method, Boundary Testing for the extremes, and Mocking and Stubbing for simulating dependencies.

Beyond unit tests, API Testing ensures smooth communication between software systems, and there’s a need to choose between code-based solutions or GUI tools like Postman for this. Lastly, UI Testing focuses on the interface’s functionality.

To go deeper, check our guide on end-to-end API testing.

test autmation pyramid vs ice cream come diagram

When automation focuses predominantly on the UI level, it’s about bug detection. However, the agile pyramid promotes bug prevention. This methodology is more beneficial as it grounds a strong unit testing base and expands to integration and UI phases.

UI automation can be achieved through Record and Playback, which is gaining traction thanks to new tools with enhanced features, or through the more traditional Scripted Testing, where tests are coded.

Record and Playback is a beginner-friendly approach. Just like recording a video, you perform a series of actions on the application, and the tool records them. Later, you can ‘playback’ these actions to see if the UI behaves as expected.

record and playback diagram

Another advanced technique is Model-Based Testing, which utilizes models for test design, either tailor-made for testing or derived from development processes. This approach allows for working at a higher degree of abstraction, without having to deal with the technical difficulties, focusing only on the model of the problem, making the tests easier to understand and maintain. 

For those aiming to enhance their testing process and outcomes, a deep understanding of these automated testing methods is indispensable.

In this post, we’ll continue discussing mainly automation with scripting, relying on tools like Record and Playback that allow you to parametrize their actions in order to follow a Data-driven Testing approach. In addition, we’ll make suggestions related to test design, and different aspects of the automation environment, considering the design will be done manually, not necessarily with model-based technique tools.

Overcoming Common Challenges of Automated Functional Testing

Automating functional tests offers a range of benefits, but it also brings forth challenges. The key is to find efficient ways to navigate these challenges. In this section, you’ll discover actionable strategies for mastering automated functional testing.

Test Maintenance

As a product evolves, maintaining automated tests becomes paramount. Especially when dealing with a growing number of tests, an organized and clear structure can make this task much easier and less chaotic.


Choosing the right naming convention for your test cases and organizing structures is a small step that can yield big results. Aim for informative yet concise names that resonate with your team and adhere to style guidelines.

Also, consider a folder structure that segregates general test cases from specific modules, making it simpler to reuse and integrate tests elsewhere. Occasionally, you might also need temporary test cases, which can be uniformly prefixed for easy identification.

Comments and Descriptions

It’s beneficial to attach a brief description to each test case, laying out its objective. Furthermore, annotating test steps and data goals can streamline the test execution and review process.

“Read Me” File

Imagine handing over a complex device without a user manual. That’s what skipping a “Read Me” file in your test framework is like. Equip your team and potential users with a comprehensive guide detailing the purpose, technologies, dependencies, instructions, and collaboration process related to your test framework.

Test Cases and Test Scripts

The eternal debate: One script per test case or a single script for multiple test cases? Both approaches have merits. A modular approach, which involves breaking down a test case into smaller, reusable modules managed by a singular script, often proves to be the most efficient. This allows for greater flexibility, maintainability, and clarity.

test case management examples

The modular approach to scripting comes with a plethora of benefits:

  • Maintenance: Simplifies updates and changes.
  • Reusability: Modules can be reused across different scenarios.
  • Flexibility: Adjustments can be made at various stages without affecting the entire script.
  • Clarity: A structured approach allows for a clearer understanding of the test flow and objectives.

To further amplify the efficiency, maintaining a matrix linking test cases with related scripts can help track the impacts of requirement changes on tests and scripts.

Avoiding False Positives and False Negatives

False results in automation can be a nightmare. Testing, in essence, should provide accurate results. So, how do we avoid these pitfalls in automated testing? The answer lies in meticulous test design, regular reviews, and understanding the root causes of false results.

We’ve explained in detail in this post how to avoid false positives and negatives in your test automation.

Testing Third-Party Services

Interactions with third-party services or applications can add another layer of complexity. Whether you’re dealing with intricate logic, web service integrations, or the proverbial rocket launch, remember that your automation tool’s primary goal is to emulate user interactions. This means, in many cases, the underlying complexities aren’t as concerning as ensuring the user interface behaves as expected.

For tasks outside the graphical user interface—like database queries or file transfers—most tools offer specific functionalities or allow custom programming. However, simulating or truly connecting to external services can be tricky. Mock Services, such as SoapU or Postman, can, can replicate external services and facilitate efficient testing.

How to Perform Automated Functional Testing

Let’s say you already have your test cases designed. You’ll start by checking the functionality inventory (or backlog or wherever you store this information) and assign a level of priority to each. Afterward, you should assign priority to each test case prepared for each of the different functionalities. This organizing and prioritizing will help divide the work (in case it’s a group of testers) and put it in order, given that grouping the test devices by some criteria, for example by functionality, is highly recommended.

Test case designs for automated testing are better off being defined on two levels of abstraction

On the one side, you have what we will call abstract or parametric test cases, and on the other hand, the so-called specific test cases or concrete test cases. 

Let’s review these concepts and apply them to this particular context. Abstract test cases are test scripts that, when indicating what data will be used, do not refer to concrete values, but to equivalency classes, or a valid set of values, such as “number between 0 and 18” or “string of length 5” or “valid client ID”. 

On the other hand, there are concrete test cases, where abstract test cases have specific values, such as, for instance, the number “17”, or the “abcde” string, and “1.234.567-8” which could be said is a valid identifier. These last ones are the ones you can actually execute and that’s why they’re also called “executable test cases”.

It is important to make the distinction between these two “levels” as you will be working with them at different stages of the automation process in order to follow a data-driven testing approach, which differs greatly from simple scripting.

For automated test scripts, data-driven testing implies testing the application by pulling information from external data sources, like databases or spreadsheets, rather than directly coding data into test scripts. This method enhances flexibility since you can add diversity to your tests merely by extending your data set.

In other words, you parametrize the test case, allowing it to run with different data. The main goal is to be able to add more test cases by simply adding more lines to the test data file.

In addition, the concept of a testing oracle helps distinguish between valid and invalid outcomes. When building your test suite, consider grouping test cases either by their functionality or their level of importance. And a word to the wise: if one function causes a test suite to stumble, diving into dependent tests might not be the best use of time.

Test Suite Design

Tools typically allow you to group test cases in order for them to be organized and run them all together. The organization can be defined by different criteria such as module or functionality and criticality. These approaches could even be combined by having crossed or nested criteria.

Defining dependencies between suites can be highly interesting, given that there are some functionalities that if they fail, directly invalidate other tests. It makes no sense to waste time by running tests that you know will fail. Meaning, why run them if they don’t bring any new information to the table? It’s better to stop everything when a problem arises attack it head-on and then run the test again until everything is working properly (this follows the Jidoka methodology).

Test Automation Plan

In the digital age, testing isn’t just an afterthought—it’s an integral part of the software development process. It’s a task that should be well thought out and planned from the beginning, even before planning development.

If you’re diving into automation, planning is your best ally. From automation setup to maintenance and from bug detection to their fixes, every step needs meticulous planning.

Managing Test Environments

Managing your test environments is non-negotiable. Think of it like setting the stage for a play. You need:

  • The application’s sources and executables.
  • Test devices and their data.
  • Updated database information specific to the testing environment.
  • Appropriate images or docker files (if using Docker.)

Here’s a tip: You might have tests with different requirements. Instead of creating many environments, consider having database backups tailored to specific tests.

However, ensuring synchronization among these elements is key. After all, when a test flags an error, it should be because of a genuine issue, not an environmental mismatch.

When and Where to Run Automated Tests

How often should you run automated tests? While “frequently” sounds ideal, practicality often dictates otherwise. Remember:

  • If tests are quick, run them all.
  • If they take time, prioritize based on risk and recent application changes.

As for where to run these tests, you’ve got options:

  • Development Environment: For developers, speed is essential. Fast feedback loops here help iron out issues quickly.
  • Integration & Testing Environment: Here, more extensive regression tests ensure previously spotted issues remain resolved.
  • Pre-production & Production Environment: Before handing off to the client, the application undergoes testing in an environment mirroring the actual production setup. Automated tests can be of great value here, ensuring the final product is as polished as possible.

Don’t forget: while UI tests are invaluable, they do take time. Hence, maximizing tests at the API level can save significant time during regression.

Automated Functional Testing Tools

Venturing into the realm of automated functional testing tools, there are a plethora of options available, each designed to cater to different testing levels – be it Unit, API, or UI.

Popular Unit Testing Tools

  1. JUnit: Predominantly used for Java applications, JUnit is a simple framework to write repeatable tests.
  2. NUnit: This is for .NET applications. Similar to JUnit in its approach, but tailored for the .NET environment.
  3. TestNG: Evolved from JUnit, TestNG is designed for high-level parallel execution.

Popular API Testing Tools

  1. Postman: A popular choice for many, Postman makes API development faster and easier.
  2. SoapUI: Tailored for both SOAP and REST API testing, SoapUI is a comprehensive tool.
  3. Rest-Assured: For Java developers, Rest-Assured simplifies the process of testing and validating RESTful APIs.

Popular UI Testing Tools

  1. Selenium: Probably one of the most well-known tools for automating web browsers. Whether you’re testing a straightforward web page or a complex web application, Selenium is an open source tool, versatile and widely adopted.
  2. Appium: For mobile applications, Appium is a top pick as an open-source tool. It allows testing across both Android and iOS platforms, ensuring your mobile apps shine regardless of the device.
  3. Cypress: Designed for modern web applications, it provides real-time reloading and automatic waiting, making UI testing smoother and more intuitive.
  4. Mabl: A low-code, auto-healing, SaaS solution that aims to simplify test creation and maintenance and make them scalable as well as spend less time fixing tests.
  5. Protractor: Tailored for Angular applications, Protractor runs tests in a real browser, interacting with the app as a user would.
  6. Testim uses artificial intelligence to speed up the authoring, execution, and maintenance of automated tests.
  7. Reflect: Reflect offers scriptless, cloud-based end-to-end testing. You don’t need to write test scripts; instead, you perform actions on your site, and Reflect records and replays them.
  8. GhostInspector: This tool lets you build or record automated browser tests and then run them continuously from the cloud.

If you’re curious about picking the right tool for your needs, dive deeper into this article.

Best Practices for Automated Functional Testing

Page Object Pattern

In our automation journey, we’ve come to realize one thing: maintainable code is gold. It’s the difference between constantly chasing updates and confidently knowing your tests will hold up. Design patterns, especially the Page Object Pattern, have been our guiding light.

Think of it this way: if a button changes in your app, would you rather rework 100 tests or just tweak one reference? That’s the magic of encapsulation.

The Page Object Pattern proposes having an adaptation layer conformed by specific objects to manage the interaction between the test cases and the application under test. To do so, you need to store the different element locators in a very organized way. If you want to see some good examples, check this.

Which problem are you solving by having maintainable code? If you have 100 test cases that interact with a certain button and the development changes its element locator, then you would need to maintain 100 test cases or at least 100 lines of code! The solution for that is very simple: encapsulation. You have to have the element locator defined in one single place and reference the element from the 100 test cases. Then, if the change happens, you only need to maintain one line of code and all your test cases will work properly. 

page object design pattern graph

Going one step further, even more encapsulation and abstraction could be added to your test architecture. You could define different test methods in the page objects, including common actions.

While the Page Object Pattern is a trusty ally, there are other patterns like Screen Play waiting to be explored, as well as any other design patterns that could be used within the framework in order to improve the maintainability of the code.

Test Design According to Goals

Setting clear goals is fundamental. When it comes to test automation, having a roadmap is essential. You will have to make certain decisions about going one way or another, selecting certain test cases instead of others and designing them with a certain approach or strategy.

Do you seek consistent testing or aim to detect those elusive regression errors earlier? Pinpointing our goals upfront saves time and sidesteps potential pitfalls down the line.

Risk-Based Testing

With our goals set, how do we decide on priorities? This is where risk-based testing shines. It guides us toward test cases that are truly crucial. We consider factors like business significance, potential financial implications, and those binding SLAs. At times, the implications are significant, especially with sensitive data at stake. With risk-based testing, we’re not just testing; we’re making informed choices.

For more on risk-based testing, check out this post.

Now, Time to Automate!

After reading this, we hope you feel confident in getting started with your functional test automation efforts. We’d like to share one last thought….

“Automation does not do what testers used to do, unless one ignores most things a tester really does. Automated testing is useful for extending the reach of the tester’s work, not to replace it.” – James Bach

We highly agree. Automation can’t replace a tester’s job, but it can make it better and more encompassing.

Not everything should be automated, and you shouldn’t try to completely replace manual testing, as there are things that cannot be automated and sometimes it is easier to manually execute something than to automate it.

In fact, if all executions could be run manually, it would probably be much better in the sense that by executing manually, other things can be found at the same time. Do remember that automated tests check, but don’t test. The problem is that some things take more time to check manually and that is why it’s convenient to automate (what’s worth automating)!

We hope this guide helps you in your endeavor to automate functional tests. Please feel free to comment below sharing your experience with automated functional testing or visit our test automation services page to learn more about how our team of automation experts can help. 

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