Lyrid Scenarios: Test Automation Tools

Tyler Au
8 minutes
June 27th, 2024
Tyler Au
8 minutes
June 27th, 2024

What Are Test Automation Tools?

Many development teams abide by the software development lifecycle (SDLC)- a process that development teams use when designing and building software. Proving to be highly efficient and resource optimal, SDLC involves the classic steps of planning, designing, and building, as well as testing and deployment. Many development teams have found that testing can be extremely taxing on their resources and team members, prompting the creation and existence of test automation tools.

Testing is an extremely slow process, with individual steps often requiring expert developers and tons of time and effort. A plethora of issues can effectively derail your testing, including hardware issues and human error. To streamline their testing, many development teams have turned towards test automation. Test automation sees development teams automating repeatable tests, collecting and analyzing data, and benchmarking that data against code standards in order to provide higher quality software.

While test automation seems straightforward, the practice is not for the faint of heart. Oftentimes, a dedicated test automation engineer would have to be onboarded in order to create the delicate automation scripts. The ideal result of these tests and scripts is to increase developer efficiency by reducing human error and freeing more time and resources. Many tests thrive by being automated, however, many have found that certain tests under the testing sphere are more optimal with manual intervention, requiring human staff.

Everything You Need to Know about Automated Testing: Types, Frameworks, and More

Test Types

With software having so many different moving parts and dependencies, it’s only fitting that there are a variety of different tests that quality assurance (QA) and software testing teams alike are conducting on a consistent basis. Some of these tests include:

Unit Tests

Unit testing involves testing the small unit of code with a block of code that verifies whether a function runs properly or not. The code block might contain sets of unit tests (or test cases), with examples of unit tests including logic checks and error checking.

Because unit tests are relatively small and low-level, they are often automated cost effectively and can be run often.

Integration Tests

Integration tests test whether different pieces of code, services, and other modules in your application work together and without consequences. This test requires tons of moving parts within the application to be running, making automation the natural choice. However, running integration tests is costly.

End-to-End Testing

End-to-end testing is essentially a user simulation, with the application and software being in a completed state. This test verifies whether user flows are working as core app functions are working.

While they are useful, these types of tests can become costly and time consuming when automated, though will also be the most reliable when automated. This is especially valuable if something as mission-critical as a user-level experience can be harmed by faulty human testing. 

Unit tests, integration tests, and end-to-end tests make up a software testing pyramid. This pyramid is a framework created to minimize the time developers spend on determining whether an update affects their overall coding.

Image Courtesy of Headspin

Exploratory Tests

Exploratory testing is seen as learning for software testers, in which individual testers parse through code to identify defects that aren’t discovered by other tests. Needless to say, these tests are usually manual.

Smoke Tests

Smoke tests are simply assessing whether code and an application works or not and can be useful when deciding whether to go through with more expensive tests.

Regression Tests

Regression tests check the quality of software after any changes are made, ensuring that applications dependent on these changes still operate smoothly. These tests are normally approached from a manual standpoint

There are countless other ways to test your software. Depending on your software needs and the insights you’re hoping to uncover, these tests might not be enough. For a comprehensive list of software tests and whether automation is optimal for them, visit this page by Atlassian

Test Automation Frameworks 

In order to achieve the best automated testing possible, an automation tester would implement test automation frameworks, compiling all of the necessary features, tools, and test scripts within a single testing environment. Test automation engineers are often in charge of the test suite directly because the automation tools are often brittle and require constant maintenance. 

Here are some common frameworks that test automation engineers use:

Linear Framework

Linear framework is the most basic framework. In a linear setting, testers create and run scripts for each test case and functionality, usually one at a time.

Suitable for smaller teams, the linear framework is ole’ reliable, but does take some time to execute fully.

Modular-Based Framework

The modular-based framework sees test cases being broken down into small parts, or modules. Because these modules are independent of each other, they are tested separately first and then tested as a whole application. While each module is run in a different scenario, a single master script runs each one, making pre planning necessary.

The modular-based approach is extremely efficient and scalable, but requires some technical knowhow because of how complex it is.

Library Architecture Framework

In the library architecture framework, tasks are grouped based on common functionality and objective within the test script, similar to a librarian grouping books based on genre. After tasks have been tested, they are stored in libraries and are quickly and easily accessible.

Proving to be the go-to framework option for when your application has similar functionality all throughout itself, the library architecture framework is reusable and scalable, though requires more technical knowhow and time to develop.

Hybrid Test Framework

Looking to try multiple frameworks? You’re in luck!

The hybrid test framework combines parts of different frameworks within a single framework, letting you pull only the features you need from specific testing approaches.

This approach is highly flexible and efficient. 

Common test automation frameworks include:


Selenium/Selenium WebDriver is a suite of tools aimed at automating web browsers and other web projects

Image Courtesy of Selenium


Appium is an open source test automation framework designed to automate UI and UI updates within web and mobile applications

Image Courtesy of Appium

Robot Framework

Robot Framework is another open source automation framework built for test automation. In particular, Robot Framework excels in flexibility, offering support of different programming languages in their extended libraries.

Image Courtesy of Robot Framework

Testing Process

As for the testing journey itself, a typical approach can look something like this:

  • Selecting the right tools
  • Defining how much automation is needed/ to what scale automation is needed
  • Planning and designing testing processes, developing test scripts and cases
  • Test execution and test reporting
  • Maintenance and updates, rolling out changes to production

Test Automation Trends in 2024

In the name of efficiency, new trends and developments within the test automation space have pushed the limits of how fast and how accurate we can test.

Here are some things to look out for within the test automation space:

Low Code Testing Platforms

The job of a test automation engineer is a hard one. From making resilient scripts and test cases to creating the right environment for a test, automation engineers certainly have their hands full in the entire testing process. The entire process is extremely time consuming as well, and requires heavy technical expertise in the field. With the number of automation engineers and software testers decreasing because of these factors, a new solution has quickly gained traction in recent years.

Low code platforms have gained popularity for a variety of reasons. While still requiring scripts and test cases, low code platforms have enabled users from non-technical backgrounds to collaborate with automation engineers through intuitive and approachable UI. This significantly speeds up testing and development cycles while keeping the same integrity of a traditional testing approach.

With testing being dependent on key engineers and teams, low code platforms enable anyone to contribute to testing processes, injecting tons of agility and flexibility into the often slow process. For teams with resource constraints that aren’t able to hire an automation engineer, having low code platforms in your testing tool belt can be key to pushing new developments out faster and reliably.

The Wide Scale Use of AI/ML

AI/ML uses are increasingly common these days, with huge advancements made in LLMs and generative AI pushing the adoption of these technologies.

Coupled with automation, AI/ML technologies significantly streamlines tons of different elements within the testing process. Some of these tasks include:

  • Test script generation
  • Task automation
  • Test result data prediction and visualization
  • Test recommendations and healing
  • Anomaly identification

By using AI/ML in automated test sequences, testing teams can deliver high quality and reliable software on a consistent basis.

From a business point of view, AI/ML within testing processes can be cost-effective if implemented properly, reducing the need for human intervention while encouraging time use in more critical facets. In addition, AI/ML usage promotes innovation within the organization, providing new ways for users to interact and evolve the tech used within testing and development itself.

Enthusiasm in Shift-Left Testing

Shift-left testing refers to conducting testing and quality checks in the earlier stages of a software development lifecycle.

Automation is certainly convenient, but can also be time-consuming to implement and costly if done wrong. A trend within the test automation space is to conduct these automated tests in a shift-left approach, identifying critical bugs early on. 

It’s said that 85% of bugs and code defects are made within the coding phase. A shift-left approach reduces the overall number of bugs throughout the early development cycle, ensuring that progressive updates can be made as software matures and that software changes are of better quality. Patching bugs earlier in the cycle can save more time and money instead of having to identify and fix bugs in a fully-fleshed out product. In addition, a shift-left approach allows development teams to become more agile, increasing your time to market as a result.

Automating with shift-left testing provides higher quality and reliable software, improving your user experience as a whole.

Image Courtesy of Palo Alto Networks

Test Automation Challenges to Consider

While automating your testing processes provides benefits such as increased flexibility, more time, and optimized resource usage, the practice is still rough around the edges in certain cases. Here are some things to consider before automating your testing:

Resource Heavy on All Accounts

Automating your testing approach has been proven to save you money down the road by reducing the overall tests you need to run and reducing the cost and frequency of failures. Despite this, the upfront costs of introducing automation can be daunting.

Automating your test approach requires a team in itself, with the average salary for a test automation engineer in the United States being roughly $96,000 per year. With automation comes the necessary tools, platforms, and frameworks to run testing. You may need to run tests a couple of times before getting them right, too. If your organization isn’t ready for automation yet, this can be extremely costly and may require more investment and resources than anticipated.

SparxIT estimates that 15 to 25% of your total software development project budget needs to be allocated towards software testing among other things. How much of that cost will be allocated towards automating your testing, and will those automations prove to work for your organization?

Resources also extend to the time and human capital required to successfully deploy automation within your testing.

In order to competently introduce automation, it takes week to months to learn how to use automation tools, depending on your solution. Coupled with the time needed to build test scripts and test cases, as well as to execute other programming, implementing and running automation can take ages initially.  This time is prolonged once you onboard more people into the automation and testing team, depending on the tool complexity and individual technical knowhow.

Automating testing requires a certain skill set that only a handful of developers possess. It’s estimated that there is a 40% shortage of developers with software testing skills worldwide. Depending on the agility your organization may need, automation at this point in time might not be the best option unless you’re willing to pay top dollar or endure the time it takes to learn automation testing.

Unstable Test Environments

Having a test environment built for the scenario you want to simulate is critical to the success of software testing. Unfortunately, building unstable test environments is common and can severely disrupt your testing. For something as costly and resource intensive as automation, an unstable environment can derail your operations and break brittle automation frameworks. In addition, having an unstable environment can lead to inconsistent testing and results, leading to more bugs and unnecessary code changes.

Approaching Automated Testing Tools with Lyrid

Low Code Approach

Creating the right framework for your tests is notoriously difficult, but hosting your testing infrastructure doesn’t have to be.

Lyrid offers an infrastructure automation platform that allows teams to run environments on cloud infrastructure. The scale at which testing must be conducted may vary depending on the project, being unable to scale might disrupt your testing processes. Lyrid is extremely scalable, with automation, managed Kubernetes, and managed databases providing everything you need to successfully automate your testing operations.

Our approach to cloud infrastructure management is simple, letting anyone in your team use the tech and tools they ended without waiting. In addition, through our intuitive UI and single pane of glass approach, everything you’ll need, from monitoring and visibility to deployment and configuration, is accessible to everyone with access in a single platform. Developers and non-developers rejoice!

Spinning Up Environments

Testing environments are as important to testing as the test scripts and test cases that are run. One misconfigured test environment can lead to bug problems, unnecessary costs, and even total testing failure.

With the Lyrid platform, you’re able to deploy instant infrastructure environments within minutes based on our premade templates and your specifications. Our environments are 100x scalable and reduce the need for manual configuration by 60% and maintenance by 80%, letting you focus on running and scaling your testing. Environments that you have found success in are also reusable with Lyrid- just define your application and configuration and we’ll take care of the standardization across future environments.

To learn more about servicing your testing approach, book a call with one of our product specialists!

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