In functional testing, testers evaluate an application’s basic functionalities against a predetermined set of specifications. Using Black Box Testing<\/a> techniques, functional tests measure whether a given input returns the desired output, regardless of any other details. Results are binary: tests pass or fail.<\/p>\n\n\n\n Functional testing is important because, without it, you may not accurately understand whether your application functions as intended. An application may pass non-functional tests and otherwise perform well. Still, if the application doesn\u2019t deliver the key expected outputs to the end-user, it cannot be considered working.<\/p>\n\n\n\n Functional tests check if the application meets specified functional requirements, while non-functional tests assess aspects like performance, security, scalability, and overall quality. To put it another way, functional testing is concerned with whether key functions are operating, and non-functional tests are more concerned with how<\/em> the operations take place.<\/p>\n\n\n\n There are many types of functional tests that you may want to complete as you test your application. <\/p>\n\n\n\n A few of the most common include:<\/p>\n\n\n\n Unit testing breaks down the desired outcome into individual units, allowing you to test if a small number of inputs (sometimes just one) produce the desired output. These tests tend to be small and quick to write and execute. Each one is designed to cover a single section of code (a function, method, object, etc.) and verify that code’s functionality.<\/p>\n\n\n\n Testers perform smoke testing to verify that the most critical parts of the application work as intended. It’s a first pass through the testing process and isn\u2019t meant to be exhaustive. Smoke tests ensure that the application is operational on a basic level. If it\u2019s not, there\u2019s no need to progress to more detailed testing, and the application can go right back to the development team for review.<\/p>\n\n\n\n Sanity testing acts as a cousin to smoke testing, verifying basic functionality to potentially bypass detailed testing on broken software. Unlike smoke tests, sanity tests occur later in the process to confirm whether a new code change achieves its intended effect. This ‘sanity check’ ensures the new code roughly performs as expected. <\/p>\n\n\n\n Integration testing determines whether combinations of individual software modules function properly together. Individual modules may already have passed independent tests, but when they are dependent on other modules to operate successfully, this kind of testing is necessary to ensure that all parts work together as expected.<\/p>\n\n\n\n Regression testing<\/a> makes sure that the addition of new code does not break existing functionalities. In other words, did your new code cause the quality of your application to \u201cregress\u201d or go backward? Regression tests focus on recent changes and ensure that the whole application remains stable and functions as expected.<\/p>\n\n\n\n Usability testing involves exposing your application to a limited group of real users in a production environment. Teams use feedback from live users\u2014who have no prior experience with the application and may uncover critical bugs unknown to internal teams\u2014to make further changes before a full launch.<\/p>\n\n\n\n UI\/UX testing evaluates the application’s graphical user interface. The performance of UI components such as menus, buttons, text fields, and more are verified to ensure that the user experience is ideal for the application\u2019s users. UI\/UX testing is also known as visual testing<\/a> and can be manual or automated. <\/p>\n\n\n\n Other classifications of functional testing include black box testing<\/a>, white box testing, component testing, API testing, system testing, and production testing.<\/p>\n\n\n\n The essence of a functional test involves three steps:<\/p>\n\n\n\n Essentially, when you execute a task with input (e.g., enter an email address into a text field and click submit), does your application generate the expected output (e.g., the user is subscribed and a thank-you page is displayed)?<\/p>\n\n\n\n We can understand this further with a quick example.<\/p>\n\n\n\n Let\u2019s begin with a straightforward application: a calculator. <\/p>\n\n\n\n To create a set of functional tests, you would need to:<\/p>\n\n\n\n For more on how to create a functional test, you can see a full guide on how to write an automated functional test for this example<\/a>.<\/p>\n\n\n\n There are many functional testing techniques you might use to design a test suite for this:<\/p>\n\n\n\n Other common functional testing techniques include equivalence testing, alternate flow testing, positive testing and negative testing.<\/p>\n\n\n\n Manual functional testing requires a developer or test engineer to design, create, and execute every test by hand. It is flexible and can be powerful with the right team. However, as software grows in complexity and release windows get shorter, a purely manual testing strategy will face challenges in keeping up a large degree of test coverage.<\/p>\n\n\n\n Automated functional testing automates many parts of the testing process, allowing tests to run continuously without human interaction \u2013 and with less chance for human error. Recent improvements in AI mean that an increasing share of the design and analysis load can be handled autonomously with the right tool.<\/p>\n\n\n\n One way to automate your functional tests is by using automated visual testing. Automated visual testing uses Visual AI<\/a> to view software in the same way a human would, and can automatically highlight any unexpected differences with a high degree of accuracy.<\/p>\n\n\n\n Visual testing allows you to test for visual bugs, which are otherwise extremely challenging to uncover with traditional functional testing tools. For example, if an unrelated change shifts a ‘submit’ button to the far right of the page, making it unclickable for the user yet still technically present with the correct identifier, it would pass a traditional functional test. Visual testing, however, would catch this bug and ensure that functionality remains unaffected by visual regressions.<\/p>\n\n\n\n Here are a few key considerations to keep in mind when choosing an automated testing tool:<\/p>\n\n\n\n Automated testing tools can be paid or open source. Some popular open source tools include Selenium<\/a> for web testing and Appium<\/a> for mobile testing.<\/p>\n\n\n\n Applitools has pioneered the best Visual AI in the industry, and it\u2019s able to automatically detect visual and functional bugs just as a human would. Our Visual AI has been trained on billions of images with 99.9999% accuracy. Applitools includes advanced features to reduce test flakiness and save time, even across the most complicated test suites.<\/p>\n\n\n\n You can find out more about the power of Visual AI through our free report on the Impact of Visual AI on Test Automation<\/a>. Check out the entire Applitools platform<\/a> and sign up for your own free account<\/a> today.<\/p>\n\n\n\nWhy is Functional Testing Important?<\/h2>\n\n\n\n
What is the Difference between Functional and Non-Functional Testing?<\/h2>\n\n\n\n
Examples of Functional Testing Types<\/h2>\n\n\n\n
Unit Testing<\/h3>\n\n\n\n
Smoke Testing<\/h3>\n\n\n\n
Sanity Testing<\/h3>\n\n\n\n
Integration Testing<\/h3>\n\n\n\n
Regression Testing<\/h3>\n\n\n\n
User Acceptance Testing (UAT)\/Beta Testing<\/h3>\n\n\n\n
UI\/UX Testing <\/h3>\n\n\n\n
How to Perform Functional Testing<\/h2>\n\n\n\n
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Functional Testing Example<\/h2>\n\n\n\n
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Functional Testing Techniques <\/h3>\n\n\n\n
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Automated Functional Testing vs Manual Functional Testing<\/h2>\n\n\n\n
How to Use Automated Visual Testing for Functional Tests<\/h2>\n\n\n\n
How to Choose an Automated Testing Tool?<\/h2>\n\n\n\n
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Why Choose Automated Visual Testing with Applitools<\/h2>\n\n\n\n