What Is Functional Testing?
While software engineering has evolved over the years, functional testing is and always will be a core component of quality testing. It is important because functional testing assesses an application’s fitness to be released to end users. In this blog, we’ll explore functional testing, how it’s used, its benefits, and its future.
What Is Functional Testing?
Functional testing is the process of validating functionality of a software application. Pass or fail is the result of a functional test, because either a feature works as designed or it does not.
Functional testing checks an application, website, or system to ensure it’s doing exactly what it’s supposed to be doing, for example:
Does the payment system on an eCommerce website prompt an error message when a user enters an incorrect card number?
Does a banking app allow a customer to log in after they enter correct credentials?
Functional testing is also associated with the term black-box testing, which is concerned with what a program does, not how.
Why Functional Testing?
Without functional testing, we can’t confirm a program meets all the requirements. For example, an app might pass non-functional and unit tests, but if the central functionality has an issue the whole app is broken. Functional testing checks that the program does exactly what it’s supposed to do based on product requirements or user stories, before its release. This is one of the ways we can avoid returning to the "software crisis" of the 1970s and 80s when developers were delivering broken software behind schedule.
Automated Functional Testing
DevOps teams around the world are constantly under the pressure to deliver better software – faster. To keep up with the growing market demands, organizations must invest time and resources into functional testing that analyzes the reliability, quality, and performance of their products. However, many companies don’t have the manpower to manually test their products exhaustively, so they choose automation.
Automated functional testing streamlines the process so it’s more efficient, repeatable, and convenient. With automation, tests can run all day without humans and with more accuracy. In addition, if the data needs modifying, someone can change the test data and run a sequential test to compare the results.
Two Techniques in Automated Functional Testing
Functional testing can be broadly divided into two categories – positive and negative testing. Let’s take a closer look at each of these categories:
This type of testing ensures that a program meets the basic requirements of the end-users and runs efficiently upon valid inputs and user flows.
This type of testing verifies that a program can handle invalid inputs or unintended flows. For example, the software should not crash when entering incorrect characters into a text field.
Benefits of Automated Functional Testing
Automated functional testing is crucial for faster software release cycles as it checks that the application is bug-free and ready for release. Developers receive multiple benefits such as:
Improving the overall quality of the application under test (AUT).
Reducing the losses and risks associated with the product.
Removing the variable of human error in testing.
Expediting the release cycle and feedback from testing back to the developers.
Expending coverage across multiple platforms through parallel automated testing.
Example: Mobile Banking App Login
A digital banking app faces major challenges related to manual testing, including delayed time-to-market, quality issues, and more. The team needed a testing solution that could perform (and automate) logging in on a real mobile device, guaranteed to work on both iOS and Android, on the latest OS version from day one.
The login has two text fields for a password and username with two buttons – login and cancel. If successful, the login page should redirect the user to their home page and the cancel button stops the login.
The username field requires five to ten characters including numbers and letters. It cannot be blank.
The password requires six to ten characters, including a number, capital letter, and a special character. It cannot be blank.
Automated functional testing could test this use-case scenario through a variety of techniques:
User-based tests ensure that all components in the system are working together simultaneously. In this case, login works across mobile devices and OS versions (iOS and Android), with various screen sizes and resolutions.
In this example, we would test the customer journey – the app loading, entering correct (positive testing) and incorrect (negative testing) credentials, redirecting to the home page, and logging out. This test guarantees that the system proceeds without any errors.
Decision-based tests check for possible outcomes when users make certain decisions, here are some examples:
If a user enters logs in for the first time, they should receive an OTP for face ID.
If a user logs in with existing credentials and chooses the “Forgot Password”, does the app lead them through the correct journey.
Boundry Value Tests
Boundry value tests analyze how the system behaves when certain data limits are in place, for example:
The mobile banking app in this example requires a password with six to ten characters, so this test checks how the app responds when a user enters less than six characters or more than ten.
What’s Next in Functional Testing?
Functional testing has taken enormous strides in recent years, and for good reason: with millions of people moving their banking, their work information, and medical records online, functional web and mobile apps are more important than ever. With that in mind, what does the future of functional testing look like? Here are some things on the horizon:
Artificial Intelligence (AI) is omnipresent across all facets of technology. Back in 2018, the AI industry was a mere $21.46 billion, now it's estimated to grow over $190 billion by 2025, according to studies. AI is the future of testing and will play a pivotal role in functional testing.
AI and ML are slowly becoming an integral part of test creation and execution. The combination of AI and Machine Learning (ML) will improve automated testing by accelerating the process and including more testing scenarios. This means that QA tools for Selenium automation and cross-browser testing must evolve over a period. The QA tools built on AI and ML technology will speed up testing for websites and applications allowing for visual validation and patterns.
With AI and ML, functional testing can run tests multiple times with stable and varied results, not only producing more scenarios but also better data that speeds along diagnosis and rapid re-testing.
Automated test maintenance and regression testing will be speedier and easier with good data and an elegantly chosen dataset can often allow for new tests without the overhead of new data. Comprehensive data like this is a valuable tool to communicate problems to developers. With AI and ML technology at the forefront of functional testing, teams will improve their reporting, data analysis, and overall confidence.
Functional Testing with Perfecto
Combining the power of flexible test authoring, cross-platform execution, and intelligent analytics into one quality platform, Perfecto helps your teams - developers, business testers, SDETs, and managers – test more, test faster, and deliver exceptional experiences. Are you ready for a more user-friendly and efficient functional testing system?