How to overcome the main challenges in test automation. Find the right tools, handle dynamic user interfaces, manage complex test cases & best practices.
Test automation reduces the time and effort spent on software testing while increasing the speed and accuracy of results. These benefits make for overall better quality software while reducing the time to release. To take full advantage, you must know the challenges in test automation and how to deal with them.
We’ll highlight your key challenges and strategies to overcome them.
Automating repetitive business processes saves time better spent on more creative tasks. This is true with test automation, as long as you know how to implement it correctly.
Here are solutions to your six biggest challenges in creating a test automation project.
Several factors affect which test automation tool and framework to use for your project. Here’s a breakdown of the critical considerations.
Type of Application Under Test
When choosing an automation testing tool, your first consideration is whether it is compatible with the application you are testing. Consider whether you need to test a desktop, web, or mobile app. Then, factor in which operating systems you need to test.
Not all tools support Windows, MacOS, Android, iOS, and Linux testing, so ensure your chosen tool can handle yours.
Finally, consider the browsers that you will test on. The browsers will largely be Chrome, Firefox, Safari, and Edge for web browsers. If you will do parallel testing across multiple platforms or browsers simultaneously, ensure your test automation tool can handle this.
Programming Languages and Ease of Use
Choose a tool using a programming language your team already knows. Having the prerequisite coding skills reduces the learning curve of using a new tool, particularly if it is the first time using a test automation tool.
You should also choose a tool that is easy for non-tech team members. Choose one with an intuitive interface and good support features.
Collaboration and Community
Choose a tool that has a good community behind it. A strong community can dramatically reduce the time it takes you to familiarize yourself with the product and troubleshoot issues as they arise. The size and activity of the community are both important, as this will correlate with how much information there is about the product. This information will come from online forums, YouTube tutorials, and blog posts.
Integrations and Features
Many tools have easy integrations with other software, such as project management tools. They can also automatically produce and send test reports to your testing teams. Consider any specific automated features you need, and you will likely find a tool to integrate them.
Scalability and Reusability
Ensure you choose a tool that can handle adequate test cases. If you are in the initial phase of development, forecast how many test cases you will need in the short to medium term and plan for that. If you use software that can only handle the amount of test cases you need now, you may have to learn an entirely new tool once your business starts to scale.
Your automation testing tools should also be able to reuse test cases and data across different environments and projects.
Budget
When planning for your budget, ensure you factor in all costs. Include the initial software purchase and operating costs such as licensing, training, and add-ons. If you have a small budget but want to try testing automation, consider trying open-source software rather than commercial in your first development cycles.
Modern software often integrates high levels of dynamic content. This makes for a more personalized user experience, but makes it harder for testing software to recognize IDs. AJAX software can also create testing issues as data is loaded asynchronously.
User interfaces using a responsive design to alter their layout according to screen size also create a challenge for automated testing. Software that uses A/B testing also provides a challenge for developers to consider when creating testing scripts and implementing your strategy.
Finally, designs regularly updated through user feedback-based iterations make it a challenge for automated testing to manage successfully.
There are a few things that you can do to prevent these issues from disrupting your automation efforts. Firstly, don’t rely on specific UI elements or layouts. Focus more on testing the functionality of your app. Secondly, choose a tool that supports object-based testing, which makes it easier to identify and interact with UI elements, even if they change frequently.
Next, implement wait conditions. These allow you to tell your testing script to wait until a particular UI element is visible before interacting with it, which helps to prevent test failures caused by dynamic content.
Finally, you can select a tool that integrates AI into its system. Artificial intelligence could be in the form of image recognition for UI elements instead of relying on dynamic IDs or AI that detects changes in the UI and automatically updates your scripts accordingly.
When dealing with complex test scenarios, you must consider multiple steps, many external dependencies, and more intricate data setups. Addressing such complexities ensures tests remain reliable and maintainable.
The first step when dealing with any large task is to break it down into smaller jobs. Modularizing your test scenario makes each chunk easier to write the script for and more straightforward to identify failure points. Isolating test data ensures that one test doesn’t depend on data created by another test. Data isolation further creates independence between modules, allowing for much more focused testing and updates.
Once you clearly define independent modules, prioritize the most critical ones to test. These will be the modules that are either the most likely to fail or have the largest impact on user experience.
You must also clearly identify your dependencies between test scenarios and test cases. Once identified, you can use mocking or stubbing to simulate the behavior of external services or systems. Then, use a test management tool to monitor and track your test cases and dependencies.
Your tests will only be as good as the test data you use. This is why developing a test data management strategy is crucial to a thriving testing environment. It involves deciding how to create, manage, and store your test data.
You can use a data generator to save time in creating realistic data for your test cases. Once the data has been generated, use data validation to ensure the test data is accurate and meets your requirements.
The data can then be stored externally as CSV files or spreadsheets to reduce the risk of errors. Data management tools help to ensure that data remains consistent and up-to-date. While version controls guarantee that errors and changes are tracked and managed effectively.
If you use sensitive data in your test samples, mask any personal information to avoid data protection breaches.
Achieving effective test coverage is essential to creating quality software. We have already covered many points that help to ensure adequate coverage. Prioritizing key modules ensures that the most critical parts of the code will be covered. Also, using an appropriate framework and incorporating visual testing lowers the risk of missing key areas, even if your code is regularly updated.
Using code coverage tools to measure the percentage of code covered by your tests gives you a quantifiable way to judge your coverage. If your percentage is low, you need to create more automation tests.
Regression testing ensures that new features and updates do not break existing functionality. Pre-written test cases allow you to automate regression testing without requiring manual testers.
The final part is to use continuous testing to execute the test cases automatically and ensure you monitor your results carefully.
CI/CD stands for continuous integration/continuous deployment, which involves frequently integrating small code changes. All developer's code is merged into one mainline several times a day. The testing process is then automated, and all code that passes the test is automatically deployed. This process automation allows for rapidly deploying many code changes daily without manual testing.
To get started, you need to choose a CI/CD tool. Ensure you select one that integrates with the automation tools and frameworks you already selected. You will then set up your pipeline, which includes building, testing, and deploying your application. Once you have created your pipeline, you will integrate all your tools and configure your CI/CD to report the results of your test cases.
Create usable and maintainable scripts for different parts of your application by changing the data inputs or parameters. This saves time and effort in maintaining your automation suite. These are also likely to be better-written and error-free, as you can invest more time into creating a reusable script due to the time you will save later.
The nature of how reusable test scripts are written makes them easier to update to reflect changes in your app. This easy adaptability means that your test environment suite remains up-to-date and effective.
Agile software developments focused on short sprints to release regular new features and product updates. The motivation is to get continuous user feedback to learn what works and what doesn’t. Short sprints of 1-2 weeks mean you never waste too much time if a new feature isn’t well-received.
DevOps goes hand-in-hand with short iterations and continuous development. It utilizes CI/CD practices to ensure code is automatically tested and approved before deployment.
Collaboration between development and testing teams increases the chances of spotting errors earlier and helps the planning team to plan for any updates they need to make to reusable scripts.
As we integrate development and testing software, it’s crucial to have communication between the teams, too. This continuous feedback between cross-department team members allows seamless testing and deployment, ensuring confidence in the quality of software releases.
Generative AI tools can be used to produce synthetic data for testing modules. Synthetic data has several advantages over a traditional dataset. You can generate data in any quantity, meaning there are never any issues as your business scales its operations. You can tailor the data you generate to your specific test case to improve the accuracy of subsequent tests.
Producing synthetic data is much more cost-effective than compiling traditional data. And you never have any privacy concerns as synthetic data does not contain any personally identifiable information. Synthetic data suits several tests, such as performance, security, and regression testing.
Cloud-based services providing on-demand test environments make automated testing available to more people. These services are ideal for companies without the personnel or technical skills to set up their environment. TEaaS offers a one-stop testing solution, cost-effectively providing scalability, agility, and reliability.
New smart devices hosting mobile apps and other IoT (Internet of Things) devices create new challenges in testing software. The diversity and complexity of these new devices can make it difficult for testers to keep up with new operating systems, screen sizes, and testing on real-world devices.
Standardizing testing through reusable scripts, automated testing, and TEaaS all contribute to staying ahead of the curve in a rapidly changing software environment. All without needing business analysts to track new devices constantly.
If you are ready to accelerate your digital transformation, get in touch today and see how BP3 can elevate your software testing. We have worked with hundreds of the largest companies in the world and successfully developed bespoke software solutions to automate every aspect of their business processes.
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