Automation testing can be a highly effective productivity booster and quality enhancer for both, your product pipeline and system development projects if implemented correctly. However, it can be a tedious task to apply the best practices when a team is just starting the implementation. In this blog, we are aiming at shedding light on some of the most common challenges that teams face as they pursue automation and possibly provide valuable solutions to overcome these challenges.
But first, let’s have a look at the most prevalent automation testing challenges:
Selecting a suitable automation testing approach
Testers need to find an appropriate test automation approach. To do so, they need to find answers to important questions like how to reduce the effort in both implementation and maintenance of test script and test suite? How to generate useful test reports and metrics? Will the automation test suites have a longer lifetime? Most times answering these important questions eases the process of heading in the right direction. In agile development, the app under test often changes through development cycles. So, designing and implementing automation test suites to correctly identify these changes and keeping the system up-to-date is a reasonable maintenance effort that is necessary and tedious. In these cases, an ideal solution would be to have a test automation solution that can detect these issues and automatically update & re-validate the test without any human intervention.
Choosing the right automation tools
Selecting the right automation tools can be problematic for QA teams because either their tools of choice don’t offer 100% test coverage or the cost of tools exceeds their test budget. Or maybe they even lack the expertise to make the most of a specific tool.
Nonetheless, if your team doesn’t know how to use a tool, you can buy an online course for your testers, or hire a consultant who can help your team master it. Reach out to the testing community if you’re still looking for the right automation tool – forums like Stack Exchange provide a rich source of information for questions that you might have in your mind.
Sometimes the tool you use might not do everything you need. In that case, you should start searching for solutions that cover areas critical to your team. If the tool you found is way out of your budget, just prepare a cost vs. benefit analysis and present your case to the executive team. An analysis of expenses coming from bugs would have been solved if you had the right tool in place. Comparing different frameworks is key to get the right fit for your automation needs.
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Comaprison Table of the Top Automation Frameworks
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Rigorous lab management
Many teams prefer to build and maintain their labs. This isn’t necessarily a bad thing. However, in-house labs are hard to manage and also expensive. With new operating systems, devices, and browser versions consistently being released, in-house labs can quickly become obsolete if not updated every once in a while, which is again an additional cost. As a result, teams end up spending a lot of time maintaining and running their lab instead of putting their time into testing. Having a cloud-based device lab is key for continuous testing unless there are some special testing requirements/scenarios with IoT, special networking (especially in the Telco space), etc.
Sorting through all the data
DevOps automation results in a huge influx of data that needs to be reviewed and analyzed. Teams often find they are swimming in a sea of data made up of log files, architecture diagrams, and test results. However, this data does contain a lot of useful information. The challenge comes in when we try to sort this data. For example, insights from data can inform R&D teams on what fixes need to be made. Making sense of all the data is a big undertaking for many teams, especially those that are not equipped with the right tools.
To achieve fast feedback, you need to be able to sort through the noise. Today, the reality of CI/CD is that it requires teams to execute tests and analyze results in minutes to understand where the problem lies and fix them at the earliest. Using test analytics can help you understand the problem and avoid it.
Knowing when to begin and stop testing
A big challenge that most if not all test managers face is knowing the answer to when to begin a test or when to stop it. You don’t want to initiate automated testing at the wrong stage of your software’s life cycle, as this would hamper the timelines of the production releases. A helpful piece of advice is to start with manual testing. Because when you start with manual testing the engineers will be able to tell when the system is stable enough and ready for automated testing. When your team is convinced that certain functionality or task can be pushed for automation, there is a better workflow as the team is aware of the timelines and is already prepared for closing tasks one after the other.
How to overcome these challenges?
- Whether a tester is an automation ninja or a manual tester with basic knowledge of the business flow, the tools should be understandable to the level of the user. Because in the end, the automation tools will allow manual testers to begin executing automation while advanced testers can focus on higher priority tests. This refers to the ability to successfully scale test automation operations.
- The solution should offer capabilities that help teams take a small, locally-run test and apply it across multiple platforms, devices, and browsers. This ensures the required scaling and test coverage.
- In today’s competitive world, teams need to have the ability to conduct a test anywhere, anytime. A comprehensive solution to this need would be to provide open access to the lab and equip teams with the right tools to run and perform tests. This ultimately helps them be adaptable and keep pace with the new releases.
- To achieve success with continuous testing and automation, teams need to be able to effectively see clear and accurate test results quickly. What’s more, they need to identify problems quickly. Remember, automation creates noise and false negatives, so teams need to be able to sort through this to provide the necessary evidence.
The only way to successfully address the top challenges in automation testing is to use a solution that combines the four components listed above. If a solution is missing one of the components, a critical part of the continuous testing process is lost. What’s more, there is a good chance team will spend a significant amount of money accounting for gaps or compromising quality.
Conclusion
While the challenges mentioned here are not the only ones in the list of challenges for automation testing. There are other challenges also such as lack of collaboration and skills. But those challenges are not hard to overcome. Whether we talk about mobile automation testing challenges or Selenium automation challenges for web apps, cloud-based testing is the solution. It gives you the flexibility and scalability needed to deliver a quality product in less time. With the right tools, skillset, and infrastructure, these challenges can be overcome over time.
