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After spending hours or even days manually testing your software, you may be wondering whether or not there’s a better way. The good news? There is.

Enter: test automation

Software test automation not only minimizes the manual work of writing test scripts, but other teams within your organization, and even your customers, can benefit from it as well.

In this blog, we’ll explain what software test automation is, which automation testing tools are best–including their benefits and use cases–and key considerations when creating a test automation strategy.

What is test automation?

What is test automation

Automated software testing is the practice of creating, running, and analyzing tests automatically (typically with specialized tooling and testing frameworks), with the goal of minimizing time-consuming and repetitive tasks experienced by manual testers. While using a software test automation platform is certainly gaining traction in the development world, many tests are still run manually, resulting in some setbacks for development teams such as:

  • Human error
  • More time spent testing software than developing new features
  • Limited number of test cases and coverage
  • Inconsistent tests

These are just a few examples of how manual testing can negatively impact an organization, which is why automation testing has been heavily adopted. Software test automation frees up time and ensures that tests are repeatable.

As with everything in the world of software, however, test automation is evolving. These days, it’s not uncommon to see even test creation becoming automated.

Types of automated software tests

A software test automation tool can write automated test scripts for various use cases. At a high level, software testing can be divided between functional testing and non functional testing.

Functional testing

Functional testing covers matching user requirements like features, while non-functional testing covers the properties of an application like its speed or security.

Functional tests can be written at various scopes. The smallest is unit testing, which isolates components of an application into small unit tests. One step higher is integration testing which is for running tests on parts of a system. The largest type of functional testing is acceptance testing which encompasses QA testing against real user needs. Smaller types, like unit testing, are more optimal for running automated QA tests, while acceptance testing is more aligned with human intervention and manual testers.

Non-functional testing

Non functional testing is also key in test design for your test suites. For example, you can use usability testing like browser testing or mobile app testing to get test data if your app works on a wide range of platforms. Performance testing can also ensure your web applications, desktop applications, and mobile applications are scaled to serve your traffic requirements. Testing frameworks like Speedscale can create test data from your own production traffic to performance test your apps.

Diagram showing different types of software testing


Benefits of software test automation

Diagram listing the benefits of test automation

Reducing human error

Manual testing is highly prone to human error. Human error can easily waste time by causing developers to debug working software, and can impact the customer experience if a manual test fails to catch a bug. Incorporating automation in your software testing process can minimize human error and bring consistency to your testing process. Additionally, implementing software test automation provides the opportunity to build test plans, effectively codifying and documenting your tests along the way–a great help for new software developers and testing teams joining your organization.

Faster feedback loops

Test automation introduces faster feedback loops, and subsequently, faster bug fixes! When manual test results take too long to return results, teams may often feel inclined to skip the tests altogether and deploy the new feature without full test coverage (we admit, this has happened once or twice…). Implementing test automation helps ensure these risky shortcuts are no longer necessary.

Increasing test coverage and scalability

Because automated tests can be run quickly and efficiently, developers can execute a large amount of test cases in a short amount of time, accelerating the testing process. A faster testing process allows developers to test more features, or even experiment with unique edge cases, ensuring that all parts of the software meet a high standard of quality.

Automated software tests cover more use cases and code. For example, a single API endpoint can be tested in several ways:

  • Positive – Valid request and expected response
  • Negative – Invalid request expected error response
  • Boundary – Test request with values at the boundaries of valid ranges
  • Missing parameters – Validate error handling of missing information
  • Extra parameter – Validate error handling of malformed request

And the list goes on… All the tests can be run for a single endpoint with a single behavior. Now think of the numerous endpoints you have and the different behaviors expected from each endpoint. Does the response change based on the user’s authorization? Does it change based on parameters like ?sort=name? Can you change the behavior with certain parameters like ?mode=compact? This is before considering how it reacts to different request bodies.

Hopefully, it’s clear that it’s unlikely to test all possible API scenarios. Although test automation doesn’t guarantee you’ll test 100% of your code, it comes much closer than manual testing. As a result, developers will spend less time “fighting fires” and troubleshooting because they’ll be notified of bugs earlier in the development process and fix them before deployment.

Even if you only use software test automation to replace existing test execution, it will likely increase your efficiency significantly.

Skip the manual scripts and large test environments

Improving application performance and stability

Software test automation allows developers to not only run tests quickly and repeatedly, but also consistently and reliably. These quality assurance checks happen much earlier in the software development life cycle, which ultimately results in much more stable software. Increasing stability, however, isn’t just about catching bugs in new code. It’s also about performing regression testing to ensure new code doesn’t impact existing functionality. Test automation lets you perform regression testing on almost every part of your application—an impossible feat with manual testing.

Automating tests also lets teams have much more control over the environment. This provides better predictability and allows developers to test their applications in a wide variety of scenarios, including very specific edge cases.

Automated software tests can also be run on a regular basis, such as nightly or weekly. For example, you might not want to run a full automated test suite every time a developer commits a new feature. In that case, it might make sense to implement regular test runs of the entire application, making sure bugs don’t accumulate over time.

All of the previous points come together to increase the quality of your software significantly. With fewer errors, higher coverage, and increased scalability, you can be much more confident in the software that you deploy. This is how companies such as Amazon are able to deploy thousands of times a day.

Saving costs

Software test automation cuts costs in three main ways; infrastructure savings, engineering hours, and opportunity costs. Because test automation allows for the creation of preview environments, it reduces the resources you need to keep running 24/7. You can spin them up when they are needed and close them down when the test is done, which can lead to huge cost savings. Also, software test automation can add help by creating powerful comparisons. It isn’t an inherent feature of test automation, but it’s possible depending on how you implement it. For example, traffic replay can consistently generate traffic to determine the optimal Kubernetes cluster configurations.

Better business metrics

Fewer bugs, more test coverage, and more time to spend on new features is music to the ears of every developer. When your software product performs well, other parts of your organization will benefit, too – here’s how:

Improved time-to-market

Quickly releasing reliable features is a major benefit of automating software tests. Faster time to market with reliable new features helps organizations react faster to market changes and get customer feedback earlier, leading to lower up-front and opportunity costs.

Higher customer satisfaction

When you thoroughly test applications, fewer bugs enter production, which improves the user experience. Any organization that prioritizes customer satisfaction should absolutely implement test automation.

Better brand reputation

Your reputation will improve as the stability of your application increases and you develop new features that satisfy customers. It’ll get even better if you respond to customer feedback quickly. Word-of-mouth will always be one of the best marketing tactics.

Increased capacity for growth

As business metrics and operations improve, your product needs to grow too, especially if you’re a SaaS platform. But unprepared growth can invalidate the benefits of test automation. Perhaps you implemented autoscaling rules because you expected a certain growth level. But your application will become unstable if you don’t factor in the time for spinning up new instances during scaling. In the best-case scenario, users will understand the situation and return later. In the worst-case scenario, users will lose interest in your product because of a negative first impression. If you’re expecting growth, implement automated tests for autoscaling.

Increased revenue and likely increased profits

Collectively, all the above benefits cause revenue increase for businesses, which is the most important advantage. Your revenue will very likely grow if you have happy customers, reliable features, and high innovation potential.

Software test automation use cases

Knowing the benefits of software test automation is only one piece of the puzzle. Arguably, it is more important to know where to implement it. Not all tests are suited for automation.  Exploratory tests, for example, are intended to explore the system.

Below you’ll find best practices and use-cases for implementing test automation.

CI/CD pipelines

The point of setting up a CI/CD pipeline is to automate the development and deployment of software. Therefore, it makes perfect sense that software test automation and CI/CD should be combined. When implementing a CI/CD pipeline, you configure it to verify that a given set of checks is passing. So, having software tests run automatically will greatly increase the efficiency of your CI/CD pipelines. Additionally, combining test automation with CI/CD provides confidence that the software you’re delivering to customers is solid.

Regression testing

Regression tests can be some of the most repetitive, predictable, and stable tests to perform. The point is to make sure that all existing parts of the application will still work as expected after introducing a new feature. Overall, regression tests are very suitable for automation because they need to be run quickly, consistently, and reliably.

Load testing

One area that has yet to see a big embrace of software test automation is load testing, but it is becoming more common. Load testing is designed to evaluate the performance and resilience of an application, making sure it can withstand a given amount of load. By combining test automation and load testing, you can make the system steadily increase the load to your application, allowing you to know exactly how much load your application is capable of handling. Be sure to keep these considerations in mind when load testing. Lastly, you may be interested to learn more about a new way to implement automation for load testing, using production traffic replication.

The key to scalable Kubernetes clusters: load test by simulating real user traffic

End-to-end testing

End-to-end testing is meant to evaluate all parts of your application from start to finish, making sure that everything works together as expected. This is accomplished by simulating real-world usage of your application and verifying that it handles regular user interactions.

The biggest hurdle in end-to-end testing is the setup. Because you need all parts of your application to work together, setting up an environment can be quite a task in itself. For this reason, many organizations choose to bypass end-to-end tests.

UI testing

Testing the user interface (UI) is traditionally done by opening up the web app and then manually clicking around to verify that everything works. Not only is this a very time-consuming and tedious process, it’s also one of the most error-prone types of manual testing. Implementing software test automation here will ensure that you discover any usability or design flaws more quickly–and consistently. In UI testing, it’s somewhat common for bugs to go unnoticed because the UI hasn’t been tested on a specific combination of device and browser. With test automation, testing for this is not a problem. Also, as with load testing, there are tools that can record user interactions in your application which you can then play back, ensuring that your tests cover real-life use cases.

Compatibility testing

Getting started with compatibility testing can be a big undertaking for any organization, especially when done manually, as the number of test cases can quickly increase. Imagine that you have a mobile application to test on two devices and two different OS versions, with ten test scenarios to run.

Diagram showing software tests across two devices with two operating systems

Now imagine that there’s another OS version and another device you need to test.

Diagram showing software tests across three devices with three operating systems

See how just two more variations to the compatibility matrix added five more devices? This is just a simple example, and in the real world you are going to have many more devices that need to be checked against your mobile applications. Because of this, compatibility testing is a perfect candidate for test automation.

Key considerations for choosing the right test automation tools

Choosing the right software testing automation tool is crucial for success no matter the situation. A good automation testing tool is simple to install, use, and maintain. Overall, it should provide a good developer experience and powerful functionality.

But what functionality should you look for? Apart from generating and executing tests, it’s vital that automation testing tools can integrate with other parts of your development process.

For example, if your test automation tool can’t integrate with your CI/CD provider, you won’t enjoy the full benefits of test automation. Yes, developers benefit from automatic test generation because it allows them to test larger parts of their applications. But the real power comes from continuous testing. For this, you need to integrate test execution into your existing workflow and validate functionality before merging a pull request.

A developer's guide to continuous performance testing

Some dev tools cover certain testing use cases for development teams, but you may need a purpose-built automation tool at times. For example, Speedscale allows you to replay traffic within a Kubernetes cluster. To send a single API request, however, you may want to use Postman. Although Postman lets you view necessary information, like request headers and parameters, manually adding the information to Postman is inefficient. Instead, proper integration allows you to export a Postman collection and import it into Speedscale, which ensures zero mistakes when transferring the request from Speedscale to Postman.

In some cases, developers prefer the interface of K6 because you can export recorded traffic and use it to create K6 tests. Or perhaps you’ve already got monitoring set up in Datadog, and you like the monitoring and reporting abilities it gives you. In that case, your automation testing tool should be able to export data to Datadog.

The point is that generating and executing tests isn’t enough, especially in a modern infrastructure like Kubernetes. Rather, integrating with other tools that enable flexibility is crucial for streamlining your development process.

Test automation can greatly improve development efficiency

Your software test automation strategy can greatly accelerate software delivery, and help you avoid user reports of bugs and errors, wasted engineering hours, and limited coverage. Although, test automation comes with a big up-front investment of time and effort, which some organizations cannot afford. As with every improvement in software development, it’s important to perform a cost-benefit analysis on any new initiative. Test automation frameworks, however, don’t need to be one complete overhaul–they can be tackled in increments. If your web applications are running in Kubernetes, you can quickly get started with automated load tests in Kubernetes as a next step.

Learn more about test automation


Service mocks: simulate third-party APIs


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