Without software testing, the software development cycle would be much shorter—and much worse! Extensive functional testing, among other things, lets developers catch and fix bugs, improve system functionalities, and ensure that any new updates will integrate smoothly into the existing software.
But should you opt for manual or automated functional testing? In this article, we'll discuss everything related to automated functional testing, including its benefits, challenges, diverse types, and the steps involved in conducting functional testing.
Functional testing is a major stage in the software development cycle. It aims to test the functionality of software builds, mobile applications, or web applications. It involves testing each application's functions to guarantee that they're working as intended at a basic level.
Examples of functions that are typically tested include:
In short, functional testing is all about ensuring every component in a piece of software works well enough. It's far, far cheaper to fix defects pre-release than post-release, so investing in extensive functional testing can be the difference between making a profit and making a loss.
Automated Functional Testing verifies an application's functionality using automated tools and scripts. In this approach, predefined test scripts simulate user interactions with the software's functions. Testing tools execute these scripts automatically, comparing the actual outcomes with expected results.
Automated functional testing has emerged as a prominent trend in recent years, offering significant advantages in software testing. Automation ensures consistent and regular execution of testing processes, independent of external factors. This reliability is crucial in functional testing, where maintaining strict control over internal processes yields more precise and reliable test results.
Now that you've grasped the concept of automated functional testing, let's delve into the different types of functional tests that can be automated.
Smoke testing involves checking for basic stability and usability, which means testing whether the app, system, or build can run without instantly crashing. At its most basic level, smoke testing checks for build validity.
Smoke tests are a precursor to other types of testing as a result of this. They make it possible to look for smaller bugs since they guarantee that your build can run in the first place. That's why smoke testing is generally a type of continuous testing - it's a good idea to check every new build for basic functionality. Fortunately, smoke tests are quick and easy to conduct and can be automated to save even more time.
The main aim of regression testing is to find and highlight bugs that have been injected into the build unexpectedly. In other words, regression testing involves looking for bugs that weren't anticipated at all in the original design.
Regression testing is also used to make sure that any problems that have been ironed out in previous versions of the build don't come back after new changes are implemented. That means that whenever an update is made to existing software, regression software verifies that problems that were fixed in older editions of the software stay, well, fixed.
Lastly, regression testing aims to stop new code modifications from negatively affecting an app's existing (and functioning) features. It ensures that the app's functionality doesn't regress, hence the name.
The idea behind integration testing is to ensure that each module within an app is working as it should. Each module (web services, APIs, databases, and so on) should also be able to be integrated into the software application as a whole without generating any new bugs. An individual component might work well on its own, but when it's put together with a bunch of others, it might not integrate smoothly - which is precisely what integration testing aims to prevent.
As you might imagine, this stage of the testing process deals with the application as a whole system instead of only looking at its individual components. Integration is a great way to ensure software quality, making sure it works as a unit rather than as a loose collection of functionalities.
Unit testing is typically done by developers themselves, even though it's often one of the later steps in the testing process. During this stage, the developers will highlight components that might cause problems (for example, by creating bugs or destabilizing builds). That means that unit testing supplements and supports other types of functional tests.
This stage of testing is particularly easy to automate. Developers only need to write the test scripts, then specify the number of test cases and let the program do the rest.
End-to-end (E2E) testing simulates the complete journey of an end user within an application. It meticulously assesses the functionality of various UI elements such as buttons, menus, navigations, and text inputs, ensuring seamless interactions. By comprehensively evaluating a user's journey from start to finish, E2E testing verifies the proper functioning of all integrations. Ultimately, this testing approach provides a robust indication of the application's readiness for production deployment.
Sanity testing, a variant of regression testing, verifies whether an application functions as intended after introducing new features or bug fixes. For instance, consider an email application adding a feature to mark emails as unread. In this case, sanity testing ensures that the marked emails appear distinct from read ones.
This testing methodology focuses on essential functionalities, determining whether further comprehensive testing is warranted. While it's extensive in breadth, sanity testing typically doesn't delve into edge cases or error scenarios. Instead, it prioritizes validating typical user interactions to ensure smooth functionality in everyday usage.
While automation significantly enhances efficiency in functional testing, it's important to recognize that certain aspects rely heavily on human judgment and creativity, making them less conducive to automation.
There are many reasons to automate your software testing. Essentially, it boils down to this: increased automation improves efficiency. It's represented clearly in this graphic, which shows some of the biggest benefits of giving tasks to AIs instead of doing them manually:
The benefits of automated functional testing are many and varied. That's why we'll consider some of the most important advantages one by one.
1. Automation speeds up the testing process - Developers have more time to deal with bugs, lowering the likelihood of creating quick fixes that don't properly address the root of the problem. In other words, speeding up the testing process means developers have the time to get things done correctly.
2. It allows for as many test cases as necessary - With automated testing, companies aren't in any way limited by the limits of their manual testers. Instead, they can increase the number of test cases covered daily to any level they need to.
3. The testing process will run like clockwork - That means that time management becomes significantly easier since everything will go perfectly according to plan in terms of how long things take.
4. It reduces reliance on testers - When you rely on testers, you may run into trouble. Human distractions—from illness to holidays—will affect your schedule. Automation, on the other hand, will always perform exactly as you want it to.
5. Improving the quality of your apps becomes easier - Testing often is a great way to boost the quality of the final products. By using automated testing, you can drive your company's growth through product quality.
6. Automation gets you all the feedback you need - All you need to do is program the script to deliver feedback on each test case and then plug in the test cases. As simply as that, your developers will have all the feedback they need at their fingertips.
To streamline the test case management process, we offer various features to simplify test case creation, execution, and analysis. Whether converting existing test cases, generating new ones, or launching tests from popular workflow software through our platform, we aim to accommodate diverse testing needs and fit seamlessly into existing workflows across all stages of the software development lifecycle (SDLC).
Additionally, we provide thorough and actionable results, including full product overviews, deep bug analysis, and incentives for critical bug discovery, ensuring high product quality and user satisfaction.
As with any step in the development process, functional testing does come with challenges. Here are a few to watch out for:
Broadly speaking, there are three distinct automated functional testing methodologies that developers can use. Each one has its own advantages and is subtly different. However, it's worth noting that considering multiple testing methodologies in your automated functional testing approach increases your chances of finding the perfect methodology for your company.
This type of testing relies on using simple 'keywords' that tell the functional testing tools exactly how to test the application. In other words, with this approach, testers enter keywords detailing which actions need to be performed on the apps being tested. It's important to note that these keywords—and the actions they trigger—are completely separate from the automated tool and the test scripts. They're simply commands that trigger certain events coded into the tools and the scripts.
A major advantage of this methodology is that it's very user-friendly. Testers don't need to modify the script whenever they want to make something specific happen, nor do they need to change anything about the automation tool itself.
As the name suggests, this type of testing emphasizes data and lets that data determine the direction of the testing. The data-driven mentality is becoming increasingly appealing as the market size of big data increases. Data is becoming a very precious resource that's worth exploiting.
A data-driven approach to automated functional testing entails storing data in external files instead of hard-coding it into the test scripts. The most popular external file type to store that data in is a spreadsheet, which can then be used to create graphs and charts to conceptualize the contents of the data.
Since the data-driven test scripts aren't bloated with data, they're much more streamlined. This means that just one script can test every data value that needs to be tested. That's a major advantage; it spares developers the effort of writing many different scripts.
Frequent testing is the simplest type of automated functional testing, which, as the name suggests, simply follows the principle of running tests as often as possible. This methodology is compatible with multiple types of software testing, such as performance or cross-browser testing. Of course, it's a lot easier to run tests more often when you're using automated tools; automation lets you run far more tests in an hour than even the most highly trained manual testers can perform in the same amount of time.
The biggest advantage of adopting a frequent testing methodology is that you'll be more likely to discover bugs sooner, which means it's cheaper and faster to address them. Another bonus point is that more test cases mean fewer bugs slip through the cracks, meaning that your resulting software will be highly streamlined. Since this methodology relies on automation, it also creates no extra work to run tests more frequently.
The process is surprisingly simple and can be completed in seven steps. These have been set out below.
The first step is to set the parameters of your functional testing process. What's the scope like? Which steps in the process are you going to automate? It's essential to have a concrete answer to both of these questions before you move forward. This is also the step when budgeting, expertise, and personnel are considered to formulate a solid plan.
Now that you've got your plan, it's time to consider which tool(s) you want to use. Some of the most popular choices for automated functional testing are Cypress, Selenium, Puppeteer, WebdriverIO, NightwatchJS, Sauce Labs, and TestSigma. The plan will heavily inform this decision. Your chosen tool should be a great fit for the tasks you'll assign it to.
You've got a plan and picked your tools. The next step is to create the framework within which all of your testing will take place. That includes outlining the testing standards, defining which practices you'll be using, and choosing between data-driven, keyword, and frequent testing methodologies. Being thorough here can save time on test maintenance down the line.
In this step, you'll install the necessary hardware and software. You'll also want to set up the testing schedule so your teams can plan around it.
The scripts will be used to run the tests themselves, so before starting tests, make sure you've got your scripts ready. They should be written according to the project's needs, which you'll have defined in steps 1 and 3.
This is the most straightforward step. All you've got to do here is run the tests exactly how you planned!
The tests are complete, and now it's time to analyze their results. At this point, you'll work with data. The data will tell you whether there are bugs and whether more testing is needed.
In order to get the most out of your automated testing, there are a few best practices to bear in mind:
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Functional testing involves running a new build through rigorous testing to remove any possible bugs. Each step focuses on a different method for rooting out errors and flaws. When automation is introduced into functional testing, every process runs more smoothly. That's because automation takes the most repetitive parts of the testing cycle and ensures they all run to the same standard of excellence. It removes the problem of human error while streamlining and improving the actual testing process.
However, while automated functional testing offers many benefits, including efficiency, repeatability, and scalability, it may not fit every organization or project. Manual testing presents distinct advantages over automated testing in certain situations:
At GAT, our goal is to optimize your product's performance, accelerate your release cycles, elevate software quality, and ensure global compatibility:
Partner with us and unlock the full potential of your software products today!
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