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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 will explore functional testing, how it is used, its benefits, and the future of this type of testing.
Table of ContentsWhat is Functional Testing? Why Functional Testing? The Need for Automated Functional Testing Two Techniques in Automated Functional TestingBenefits of Automated Functional Testing Automated Functional Testing Example: Mobile Banking App Login What Is Next in Functional Testing? Bottom LineTable of Contents1 - What is Functional Testing? 2 - Why Functional Testing? 3 - The Need for Automated Functional Testing 4 - Two Techniques in Automated Functional Testing5 - Benefits of Automated Functional Testing 6 - Automated Functional Testing Example: Mobile Banking App Login 7 - What Is Next in Functional Testing? 8 - Bottom Line
Functional testing is the process of validating the functionality of a software application to ensure that it is working properly. Functional tests result in 'pass' or fail,' because either a feature works as designed or it does not.Functional testing is also associated with the term black-box testing, which is concerned with what a program does, not how.
Functional testing is the process of validating the functionality of a software application to ensure that it is working properly. Functional tests result in 'pass' or fail,' because either a feature works as designed or it does not.
Functional testing is also associated with the term black-box testing, which is concerned with what a program does, not how.
Functional testing checks an application, website, or system to ensure it’s doing exactly what it’s supposed to be doing, for example:
Without functional testing, we can’t confirm that 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.
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.
Functional testing can be broadly divided into two categories – positive and negative testing.
Let’s take a closer look at each of these categories (read more about all types of functional testing here):
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.
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:
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.
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:
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.
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.
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DevOps Chief Evangelist & Sr. Director at Perforce Software, Perfecto
Eran Kinsbruner is a person overflowing with ideas and inspiration, beyond that, he makes them happen. He is a best-selling author, continuous-testing and DevOps thought-leader, patent-holding inventor (test exclusion automated mechanisms for mobile J2ME testing), international speaker, and blogger.
With a background of over 20 years of experience in development and testing, Eran empowers clients to create products that their customers love, igniting real results for their companies.