Top 10 Challenges in Automation Testing and their Solutions

Anushree Chatterjee

As the world becomes digital, there’s tremendous pressure on IT to deliver quality outcomes at lightning speed. Websites and applications must be up and running around the clock, with no room for glitches. This makes testing the gatekeeper. Clearly, manual testing cannot keep up with this constant time crunch, and hence, automated testing is being increasingly relied upon.

However, automated testing isn’t as smooth and easy as it may sound. Though it saves time, eliminates repetitive tasks, and promotes less time to market, it is riddled with challenges. In this post, we will review the top 10 challenges that automation testing faces and examine their solutions.

Top 10 challenges in automation testing

In this section, we will talk about the top 10 automation testing challenges, their examples, and possible solutions.

1. Setting realistic expectations

The allure of automated testing can sometimes lead to unrealistic expectations about what it can achieve. Automation excels at repetitive tasks but can’t replicate human intuition and ad-hoc testing. Complex scenarios, edge cases, and user experience (UX) testing are still best suited for manual testing. Automation testing isn’t a magic bullet. It’s meant to complement manual testing, not replace it entirely. However, an intelligent automation testing tool such as testRigor lets you automate exploratory testing as well.

If you’re aiming for 100% coverage, then that’s just not going to happen because not all functionalities are ideal candidates for automation. Factors like cost, maintenance effort, and the likelihood of change should be considered when selecting tests for automation. Read: Which Tests Should I Automate First?

Unrealistic expectations could look like this:

• “Automating Everything” is like expecting to automate every single test case, which can lead to a bloated, unmanageable test suite.
• “Automation Guarantees Bug-Free Software”, automated tests verify specific functionalities based on pre-defined conditions. They might miss unexpected bugs or regressions in logic.
• The “Set it and Forget it” Approach. This is an interesting one. Automated tests need maintenance as the application evolves. It’s unrealistic to think they’ll run flawlessly forever.

Solutions

You can set realistic expectations by following these ways:

• Focus on the right targets: You should identify repetitive, regression-prone test cases that are well-defined and have low maintenance needs. These are your prime candidates for automation.
• Define success metrics: Set realistic goals for automation. Focus on metrics like improved test coverage for core functionalities, faster regression cycles, or reduced manual testing effort. Read: QA Metrics to Improve Your Software Testing.
• Communicate openly: Discuss automation’s limitations with stakeholders right from the start. Emphasize its role as a complementary tool to manual testing, not a replacement. However, testRigor is a Test Automation Tool For Manual Testers.
• Start small and scale up: Begin with a small set of well-defined tests and gradually expand the automation scope based on success. Remember that automation should make testing easier rather than add to your workload. Know more about test scalability.
• Measure ROI: Track the return on investment (ROI) of automation. This could include metrics like time saved, bugs caught by automation, or reduction in manual testing effort. Read: How to Get The Best ROI in Test Automation.

2. Selecting the right tool and testing stack in automation testing

There are numerous automation tools, each with its strengths and weaknesses. Choosing the wrong one can lead to wasted resources, inefficiency, and heavy test maintenance. But not all tools excel at everything. A tool ideal for web applications might not be suitable for mobile app testing or API automation. The learning curve for different tools varies. Choosing a tool your team can’t grasp effectively hinders automation efforts. Read: How to Build a Test Automation Framework.

Examples of poor choices could be using a web automation tool like Selenium to test desktop applications, choosing a generic, open-source tool for testing a complex and niche product, or selecting a complex scripting-based tool for a team with limited or no programming skills. Here are the 11 Reasons NOT to Use Selenium for Automation Testing.

Solutions

Here are some ways in which you can ensure that the tool you choose suffices your needs:

• Analyze project requirements: Clearly define what needs automation. This includes the application type (web, mobile, desktop), testing needs (functional, regression, API), and supported platforms (browsers, operating systems).
• Consider team skills & preferences: Evaluate your team’s existing programming knowledge and comfort level with scripting languages. Opt for tools that align with their skillset or consider training opportunities.
• Research and compare tools: Research popular tools that cater to your project requirements. Explore free and open-source options alongside commercial tools. Here are the Top 7 Automation Testing Tools to Consider.
• Prioritize tool features: Identify features crucial for your project, like cross-browser compatibility, mobile testing capabilities, reporting functionalities, and ease of integration with existing CI/CD pipelines.
• Proof of concept (POC): Conduct POCs with shortlisted tools to evaluate their usability, performance, and suitability for your team.

3. Inadequate testing infrastructure

Writing and running automated tests isn’t enough, especially in thoroughly integrated environments that follow Agile and CI/CD. Automated tests often require to be run on various test environments like dev, staging, and production to simulate real-world conditions. Setting up and managing these environments can be resource-intensive. Moreover, as the number of tests and complexity increase, the testing infrastructure needs to scale efficiently. Limited resources or outdated infrastructure can lead to slow test execution times and bottlenecks.

Examples of inadequate infrastructure can be seen in scenarios where tests are being run on a single environment, leading to scheduling conflicts and hindrances in parallel test execution. Other situations could be when automated tests are run on outdated hardware, leading to a rise in test execution time, or having network connectivity issues that can disrupt communication between test scripts and test environments, leading to test failures or incomplete execution.

Solutions

Here are some ways to build a robust testing infrastructure:

• Leverage cloud-based solutions: Cloud platforms offer scalable and readily available resources for setting up test environments. This eliminates the need for in-house infrastructure management.
• Containerization technologies: Docker containers provide a lightweight and portable way to package test environments, simplifying deployment and management.
• Test data management tools: Utilize tools for managing test data effectively. This includes data generation, masking, and version control to ensure data consistency and avoid test failures. Read: Optimizing Software Testing with Effective Test Data Management Tools.
• Test automation frameworks: Choose frameworks that can help manage test environments and resources efficiently.
• Invest in network monitoring: Proactively monitor network performance to identify potential issues and ensure smooth test execution.

4. Need for upfront investment

One of the biggest hurdles in adopting automated testing is the initial investment required. Setting up a robust testing infrastructure, whether on-premise or cloud-based, incurs costs for hardware, software licenses, and potentially additional resources like cloud storage. Many automation tools require licensing fees, especially for commercial options with advanced features.

Your team might need training on the chosen automation framework, scripting languages, and best practices. This can involve internal training resources, external training programs, or acquiring online learning materials. The much-feared test maintenance tends to drive the cost further up as developing and maintaining automated test scripts requires dedicated development effort. This can strain existing resources or necessitate hiring additional testers with automation expertise.

Solutions

By adopting a strategic approach and focusing on the long-term benefits, you can overcome the initial investment hurdle and unlock the value proposition of automated testing for your project. Here are some ways to do it:

• Plan your budget: It is a good idea to plan your expenses in automated testing. For example, if you know your budget is small for skilled resources, then opt for tools that have a small learning curve, like no-code tools. Read: How to Save Budget on QA.
• Start small and scale up: Begin with a small set of critical test cases to automate. This minimizes the initial investment and allows you to demonstrate the value of automation before scaling up.
• Open-source tools for small projects: Consider using free and open-source tools if you have a small project at hand. While they require more technical expertise, they eliminate licensing costs and offer a great starting point.
• Focus on ROI: Calculate the potential return on investment (ROI) of automation. Consider the time saved on manual testing, reduced defect leakage costs, and improved software quality. Use this data to justify the initial investment to stakeholders.
• Phased implementation: Break down the automation implementation into phases. This allows for a more controlled investment and helps prioritize the most critical functionalities for automation.
• Reskilling existing testers: Invest in training your existing QA team on automation concepts and tools. This leverages existing expertise and reduces the need for external hiring.

5. Finding the right skill set

The transition from manual testing to automation testing requires a different skill set. There are various aspects of automated testing that testers need to be familiar with. Skills like programming to work with testing frameworks that need coding, understanding and working with the automation tools, and other testing concepts like Page Object Model(POM), data-driven testing, and API testing are fundamental to robust testing. If manual testers are going to automate test cases, then they need to adapt from the free-flowing exploratory and UX testing styles to a more structured and logic-driven approach.

Some examples of these can be seen when a team accustomed to black-box testing might struggle to adapt to the white-box testing approach often needed for API automation, or testers familiar with web application testing might not have the expertise to automate mobile app testing using mobile testing frameworks.

Solutions

You can build your team’s skillset through the following ways:

• Invest in training: Provide training programs on automation frameworks, scripting languages, and best practices in test automation. This can be through internal training resources, online courses, or workshops.
• Reskilling existing testers: Upskilling your existing QA team is often more cost-effective than hiring new personnel. Training programs can help them bridge the skill gap and leverage their domain knowledge in an automation context.
• Hire for automation expertise: If the project demands a high level of automation or your team lacks the bandwidth for training, consider hiring testers with prior experience in automation frameworks and scripting languages.
• Build a hybrid team: A well-rounded team might have a mix of testers with strong manual testing skills and others with automation expertise. This allows for collaboration and knowledge sharing.
• Focus on automation-friendly tools: Consider low-code or codeless automation tools if your team has limited programming experience. These tools offer a more user-friendly interface for building automated tests.

Read: Transitioning from Manual to Automated Testing using testRigor: A Step-by-Step Guide.

6. Maintaining test automation suites

Automated tests are valuable assets, but they require ongoing maintenance to ensure their effectiveness. This maintenance work tends to crop up due to the following reasons:

• Application changes: Frequent application updates can break existing automated tests. These require maintenance to adapt to the new functionalities or UI changes.
• Test flaky-ness: Flaky tests are unreliable and produce inconsistent results. They can waste time investigating false positives and hinder test suite credibility.
• Code maintainability: Poorly written or undocumented test scripts become difficult to understand and maintain over time. This can lead to debugging challenges and hinder future enhancements.
• Evolving requirements: As project requirements evolve, the test suite needs to adapt to cover new functionalities or adjust existing test cases to reflect changes in user stories.

Solutions

By following the below-mentioned practices, you can establish a sustainable approach to maintaining your test automation suite.

• Design for maintainability: Write clear, concise, and well-documented test scripts from the beginning. Utilize modular design principles and Page Object Model (POM) for better maintainability.
• Automate what’s stable: Focus on automating tests that target core functionalities and are less prone to change. This minimizes maintenance effort after application updates.
• Version control: Use version control systems like Git to track changes in test scripts and revert to previous versions if necessary. This simplifies troubleshooting and collaboration. Read: How to Do Version Controlling in Test Automation.
• Test refactoring: Regularly review and refactor test scripts to improve readability, eliminate redundancy, and ensure they align with evolving application functionalities.
• Continuous Integration (CI): Integrate automated tests into your CI pipeline. This allows early detection of test failures after code changes and facilitates faster debugging. Read: Continuous Integration and Testing: Best Practices.
• Execute in different environments: Run automated tests in various environments (dev, staging, production) to catch regressions early on and ensure broader test coverage. Read: Testing in Production: What’s the Best Approach?
• Opt for good tools: It’s a good idea to choose a test automation tool that is reputed to reduce maintenance costs. Look for those.

7. Communication and collaboration issues

Effective communication and collaboration are crucial for the success of any testing initiative, and automation testing is no exception. Quite often, development, testing, and operations teams often work in silos, leading to a lack of understanding of each other’s processes and priorities. Pair it with ambiguous or poorly defined requirements; you will get automated tests that don’t align with actual user needs or expected functionalities.

During the testing process, if there was little to no documentation done, then this inadequate documentation of test scripts and automation frameworks can hinder collaboration and knowledge sharing between team members.

Solutions

Here are some solutions to foster effective communication and collaboration:

• Early collaboration: Involve testers in the early stages of development to understand requirements and ensure automated tests align with project goals.
• Clearly defined roles and responsibilities: Define clear ownership of test automation efforts, including development, execution, and maintenance.
• Regular communication channels: Establish regular communication channels (meetings, chats) between testers, developers, and operations teams to discuss automation efforts, challenges, and upcoming changes.
• Comprehensive documentation: Maintain comprehensive documentation of test scripts, frameworks used, and expected functionalities. This aids in knowledge sharing and onboarding new team members.
• Joint ownership: Promote a culture of joint ownership where developers and testers collaborate on building and maintaining the automation suite.
• Test automation champions: Identify and empower test automation champions within the team to spearhead communication efforts and guide the automation process.
• Utilize collaboration tools: Leverage collaboration tools like project management platforms or code repositories to share information, track progress, and facilitate discussions around test automation.

Read: How to Align Software Engineering with Business Goals.

8. Browser and device compatibility

In today’s diverse technological landscape, ensuring your web application functions flawlessly across different browsers and devices is crucial. Automated testing presents unique challenges in this area. The existence of numerous web browsers (Chrome, Firefox, Safari, Edge, etc.) with varying rendering engines and functionalities makes achieving perfect cross-browser compatibility difficult. Add to this the ever-growing array of devices (desktops, laptops, tablets, smartphones) with different screen sizes, operating systems, and browsers further complicates compatibility testing. Users often have different browser versions installed, and some might not update frequently. Ensuring a responsive web design adapts seamlessly to various screen sizes and resolutions requires thorough testing across different devices. Read: Cross-platform Testing.

Examples of these compatibility issues are a web form might appear distorted or have misaligned elements when accessed on a specific browser version, interactive features like sliders or carousels might not function properly on certain mobile devices, a critical functionality might work flawlessly on Chrome but break down entirely on Safari due to browser-specific rendering differences, text might overflow or become illegible on smaller screens due to inadequate responsiveness of the web design.

Solutions

You can ensure your web application delivers a seamless user experience across different platforms, leading to higher user satisfaction and website adoption by using the following ideas:

• Prioritize based on usage statistics: Analyze website traffic data to identify the most commonly used browsers and devices by your target audience. Focus testing efforts on these popular configurations.
• Utilize infrastructure provider tools: Cloud-based testing platforms like testRigor provide access to a vast array of real browsers and devices while testing, eliminating the need for physical device maintenance.
• Emulators and simulators: Mobile device emulators and simulators can be helpful for initial testing, but they might not replicate real-world device behavior perfectly. Use them in conjunction with real device testing.
• Cross-browser testing frameworks: Many test automation frameworks allow you to write test scripts once and execute them across different browsers and devices using grid configurations. Read more: Cross-browser Testing.
• Responsive design testing tools: Tools like Google’s Mobile-Friendly Test can help identify responsiveness issues and ensure your web design adapts effectively to various screen sizes.
• Test early and often: Integrate browser and device compatibility testing into your automation process from the beginning. This helps catch issues early on and prevents regressions during development.

9. Issues with test data

Automated tests often rely on test data. However, procuring this data is often times a challenge, mainly due to the following reasons:

• Test data inconsistency: Automated tests often rely on specific data sets to function. Inconsistent or inaccurate test data can lead to test failures, even if the application logic is correct.
• Data management overhead: Managing large volumes of test data, especially for complex applications, can be a time-consuming and resource-intensive task.
• Data security concerns: Certain test data might contain sensitive information. Ensuring secure storage and access controls becomes crucial to prevent data breaches.
• Limited reusability: Test data specific to a single test case might not be easily reusable for other scenarios. This can lead to test script duplication and maintenance challenges.

Solutions

Here are some solutions to mitigate the challenges of data reliance:

• Data-driven testing: Utilize data-driven testing frameworks that separate test logic from test data. This allows you to define test cases once and use different data sets for each iteration, improving reusability and reducing script duplication.
• Test data management tools: Invest in test data management tools that facilitate data creation, masking of sensitive information, version control, and easy data access for test scripts.
• Leverage external data sources: Consider using external data sources like APIs or databases to populate test data dynamically. This reduces the need to maintain large static datasets within your test suite.
• Parameterization: Employ parameterization techniques to allow test scripts to accept data as input during execution. This enables running the same test with different data sets for broader test coverage.
• Mock data generation: Utilize mock data generation tools to create realistic but anonymized data for testing purposes. This helps avoid security concerns and ensures data consistency.
• Focus on independent tests: Whenever possible, strive to design automated tests that are less reliant on specific data values. This improves test case maintainability and reduces the impact of data changes.

Read: Optimizing Software Testing with Effective Test Data Management Tools.

10. Defining a test automation strategy

A crucial first step in the test automation process is defining a strategy. Without clear goals for automation, it’s difficult to determine which tests to automate and the level of automation to achieve. Automating everything is neither feasible nor desirable. Prioritizing which functionalities to automate based on factors like risk, complexity, and regression frequency is crucial. The automation strategy should align with the specific project requirements and development lifecycle. A one-size-fits-all approach might not be effective. Effective automation requires investment in tools, training, and ongoing maintenance. A well-defined strategy ensures resources are allocated efficiently based on project needs and expected benefits.

Solutions

By following these guidelines, you can develop a well-defined automation testing strategy that maximizes the return on investment (ROI) from your automation efforts:

• Define automation goals: Set clear and measurable goals for automation, such as improved test coverage, reduced testing time, or faster feedback cycles.
• Prioritize test cases: Analyze your test suite and prioritize functionalities for automation based on factors like risk, complexity, execution time, and regression frequency. Read more about Risk-based Testing.
• Align with project needs: Consider the project’s development lifecycle, release cycles, and testing methodologies when defining the automation strategy.
• Resource allocation: Be realistic about available resources (tools, budget, personnel) and allocate them strategically to achieve your automation goals.
• Start small and scale up: Begin with a small set of well-defined, high-value test cases for automation. As you gain experience and demonstrate success, you can gradually scale up automation efforts.
• Measure and adapt: Continuously monitor the effectiveness of your automation strategy. Track metrics like test coverage, execution time, and defect detection rate. Use this data to identify areas for improvement and adapt the strategy as needed.
• Collaboration is key: Involve stakeholders from development, testing, and operations teams in defining the automation strategy. This fosters collaboration and ensures everyone aligns with the goals of test automation.

Here is a useful Test Strategy Template.

Maximizing outputs with modern testing tools

You must have realized by now that choosing the right automation testing tool can determine your success in overcoming the challenges discussed above. A good tool should reduce your work by making test case writing, execution, and maintenance easier. In fact, you can find great no-code, cloud-based solutions that eliminate the need to extensively train your workforce in coding and working with complex setups. Read: Codeless Automated Testing: Low Code, No Code Testing Tools.

testRigor to combat test automation challenges

One such tool that can turn the tide in your favor in test automation is testRigor. It is one of the best solutions there is out there as it uses generative AI through and through to let you write test cases in plain English language, without worrying about implementation details of web/UI elements like XPaths, CSS, or POM. This means that anyone with a basic understanding of writing test cases can compose automation test cases, improving collaboration among teams while reducing the learning curve drastically. Read more about AI In Software Testing.

Besides making test case writing easy, testRigor uses AI to do a lot more. Through testRigor’s use of AI, flaky test runs are avoided, making test maintenance negligible. testRigor enables you to test web, mobile (hybrid, native), API, and desktop apps with minimum effort, cost, and maintenance. Its AI-powered capabilities let everyone on your team create and execute plain English test cases and achieve excellent test coverage.

There’s a lot more you can do with testRigor. Take a peak at all of the tool’s offerings over here.

Frequently Asked Questions (FAQs)

Evaluate your application’s technology stack, your team’s skill level, the community and support available for the tool, and your budget. Consider tools that integrate well with your existing systems and processes. Opt for those that are agnostic to the underlying codebase and easy to use, like testRigor.

Test scripts should be reviewed and updated with every significant change to the application they are testing. This ensures that they remain effective and do not become obsolete.

Use cloud-based services for test execution to handle increased demand flexibly. Organize your tests logically and maintain clear documentation to manage growth effectively. Know How to Setup OKRs Properly.

Focus on key platforms and devices that represent the majority of your user base. Use tools that support multiple platforms and automate repetitive tests across these platforms to ensure broad coverage.

Calculate the expected return on investment (ROI) by considering factors like reduced time to market, lower bug rates, and decreased need for manual testing. You can start with a pilot project to demonstrate the benefits before full-scale implementation. Here is an ROI Calculator for Nocode Test Automation.

You can utilize metrics like the reduction in regression testing time, the number of defects found, the coverage of critical functionalities, and improvements in release cycles.