The Top 10 Test Automation Challenges

It’s difficult for any IT organization to execute DevOps effectively without test automation. However, it’s often easier said than done. Overcoming the challenges of automated software testing can end up slowing down product delivery and impacting quality, the exact opposite of the overall goal of DevOps. Let’s go through some of the biggest challenges developers face when it comes to test automation and ways to overcome them. 

1. Selecting the Right Tools

The sheer number of automation testing platforms on the market can quickly become overwhelming. Making the wrong choice can bog teams down in inefficiencies and waste time and money. The resulting failed automation initiatives can lead to reluctance to try them again at a company-wide level. 

So, what can teams do to ensure they find the right product? That starts with assessing a project’s specific needs. They should look at the technologies involved, including whether this is a web or desktop application. A tool like Selenium can be helpful for both types. Teams should also consider any required supporting cloud services. 

Once you understand your technology, it’s time to start figuring out the test types you’ll need to automate, including:

• Unit tests
• Functional tests
• Performance tests
• Security tests

Now, you can start evaluating the features and capabilities provided by various platforms. It helps if they have intuitive interfaces. Codeless platforms can be easier to adopt as they don’t require knowledge of a specific language. That makes using the same tool easier for users from various development backgrounds. 

Other things to consider as you choose your test automation tools include:

• Support for testing across different platforms and devices
• Ability to handle modern practices like Agile methodologies
• The pros and cons of using open source vs. commercial tools 
• Whether there’s adequate vendor support
• How much it costs to own the tool, including licensing and subscription fees
• Available security features

2. Finding Qualified Automation Engineers

Companies need qualified automation engineers to oversee the development, implementation, and maintenance of automated testing frameworks. As more organizations turn to Agile methodologies and DevOps practices, there’s a high demand for those with that background. 

Those capable of handling this role typically come from a programming background and are proficient in languages like Python, C#, or Java. Ideal candidates also understand DevOps and Continuous Integration (CI) Continuous Delivery (CD) pipelines. 

Companies can try to overcome this talent gap by:

• Setting up apprenticeships for new college graduates to learn test automation
• Offering competitive bonuses and salaries
• Providing comprehensive benefits packages
• Taking advantage of advanced recruitment strategies like appealing directly to qualified candidates on networking sites like LinkedIn

Another way organizations can overcome this challenge is by developing candidates internally. Setting up in-house training programs to build employee skills can pay off over the long term. Businesses can also encourage qualified personnel to pursue certification courses offered by bodies like ISTQB or ASTQB. 

Taking the time to grow talent organically can ensure that companies always have a qualified pipeline of talent they can tap for projects requiring test automation engineers. These skills can also pay off in other areas of IT. 

3. Managing Test Data

Data privacy and protection have become a big concern as more information becomes available online. Many companies use the internet to collect test data to validate the functionality and performance of applications. Handling that information correctly often brings numerous challenges that can impact the effectiveness of test automation. 

For example, if you’re using data scraping tools to bring in data, you can run the risk of gathering information protected under regulations like GDPR, CCPA, and HIPAA. Any mishandling of personally identifiable information (PII) can lead to serious legal repercussions. 

For that reason, organizations need automation tools capable of providing:

• Data masking and anonymization: Obscures sensitive information to look realistic without exposing sensitive data.
• Encryption: Secures data to prevent unauthorized viewing at rest or in transit.
• Access control: Restricts access to data to authorized personnel only.

The sheer volume of information available in today’s world requires the management of large volumes of test data. Companies need tools to create smaller datasets that maintain the characteristics required for effective testing. Organizations should also consider setting up a synthetic data generator that does not contain sensitive information. 

Other data management considerations include:

• Keeping data up-to-date and relevant
• Making sure to maintain data dependencies across different environments
• Ensuring data remains consistent and available across different stages of the development lifecycle

4. Continuous Integration and Continuous Deployment (CI/CD)

Modern IT shops use CI/CD processes to deliver quality products quickly and efficiently. However, many shops struggle to maintain stable and reliable tests in CI/CD pipelines.  One way to overcome that is by making every test independent so they don’t interfere with each other.

It’s also a good idea to perform a root cause analysis to locate underlying test issues and perform fixes. You should also add a retry mechanism to deal with transient failures and reduce the impacts of bad tests in CI/CD. 

Any increase in project size can cause the number of automated tests required to grow substantially. That typically leads to longer build times and a slower feedback loop. Ways to overcome that include:

• Prioritizing critical tests by running them first to ensure faster feedback
• Using parallel test execution to help distribute test load across various machines to reduce execution time
• Performing incremental testing, where teams only run tests affected by recent changes

5. Maintaining Test Scripts

Teams often use test scripts to ensure the reliability of automated tests. As applications evolve, those scripts need updating to reflect those changes. Otherwise, it’s hard to ensure accuracy in evaluating an application. 

If you’re dealing with an application that undergoes constant changes, consider using modular scripts that break tests down into reusable components. This reduces the number of changes required when the application is updated. 

Tools are also available that automatically update test scripts based on where you make application changes. Many use AI and machine learning to adapt scripts to new UI updates. 

6. Scaling Test Automation

Dealing with a growing number of automated tests can lead to longer execution times and larger overhead. One way to overcome that is to perform constant test suite reviews to remove redundant or obsolete tests. This leaves you with a leaner test suite that covers your core functionalities.

You also need infrastructure capable of handling an increased number of automated tests. Cloud services offer much flexibility in quickly scaling your environments to accommodate different loads. 

Teams should also look into distributing testing across different machines or nodes simultaneously. In addition, it helps to centralize test suites in a single platform to simplify data provisioning and maintenance needs. 

7. Testing Across Multiple Platforms

Many IT organizations need to provide support for multiple operating systems (Windows, OS, Linux), devices, and browsers. This complicates test automation because each platform has its quirks and characteristics that affect application behavior. 

The best way to confront that challenge is by investing in cross-browser testing tools that work within multiple browsers and devices. It also helps to use responsive design principles to ensure that applications adapt to different screen sizes and resolutions. 

Other ways you can address concerns across different platforms include:

• Setting up device labs to test the performance of commonly used devices
• Using emulators to perform initial testing to replicate different device conditions
• Relying on automated testing suites to cover the essential functions of different devices 

8. Changes in Technology

It’s hard for even the most experienced IT professional to keep up with every new change. There’s always a new framework or testing tool promising to revolutionize how you perform testing. 

The best way to address this challenge is to make learning an integral part of the work environment. The culture should encourage continuous learning. Companies can do this by providing teams access to webinars and training that update them on the latest and greatest. 

It’s also a good idea to perform regular evaluations on new platforms and frameworks to determine if they would fit a new project well. That includes conducting proof of concepts (PoCs) to determine how practical it would be to adopt a new solution. Other considerations should include determining if a new tool integrates easily with existing technology, including legacy systems. 

9. Measuring Automation Success

Most companies’ most significant challenge in determining automation success is determining which metrics to use. Look for those that align directly with company objectives and other organizational and testing goals, which can include:

• Overall test coverage
• Defect detection rate
• Test execution time

You can also develop customized metrics for your project and stakeholders’ needs. If you’re looking for ROI, perform a cost-benefit analysis that compares the cost of using automation tools with the benefits provided, including reduced testing time that frees up resources for other projects. 

10. Balancing Speed and Quality

Teams can avoid getting bogged down in large, complex test suites by avoiding running all tests. Instead, focus on those tests impacted by recent code changes. Allocate more resources to testing the most critical areas of an application that are prone to defects. That helps maximize your testing efforts while ensuring adherence to quality. 

Another way to balance speed and quality is by segmenting automated tests running in the CI/CD pipeline. Each segment should run different test types at various stages. Make sure your feedback loops are set up to locate and address issues quickly. 

Forget About Choosing Between Speed and Quality With Ranorex

Ranorex provides teams with everything needed to automate their test suites fully. Get your free trial of Ranorex Studio and experience the benefits of adopting Ranorex in your organization.