Automation testing challenges and their solutions pCloudy

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Automation testing challenges and their solutions

Automation testing can be a highly effective productivity booster, and a quality enhancer for your product pipeline or system development projects if done correctly. But it can be difficult to apply best practices when a team is just starting this transformation. We’ll shed light on the most common challenges that face teams as they pursue automation efforts and also how to overcome these challenges. hh

Let’s have a look at the most prevalent automation testing challenges:

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It’s vital for testers to find an appropriate test automation approach. In order 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 automation test suites be having a long lifetime? 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 keep up-to-date quickly with reasonable maintenance effort is necessary. It is ideal to have a test automation solution that can detect these issues to automatically test without any this is an external link.

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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 lack the expertise to make the most of a specific tool. 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 are a rich source of information.

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Sometimes your tool might not do everything you need. In that case, you should start searching for multi-tool 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 this is an internal link case to the executive team. An analysis of expenses coming from bugs that would have been solved if you had the right tool in place is bound to work to your favor.

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There are still teams that prefer to build and maintain their own labs. This isn’t necessarily a bad thing. This text is bold. But, in-house labs are hard to manage and they are expensive. With new operating systems, devices, and browser versions consistently being released, labs can quickly become out of date. As a result, teams can spend a lot of time maintaining and running their lab as opposed to testing. Having a cloud-based lab is key for continuous testing unless there are some special testing requirements/scenarios with IoT, special networking (especially in the Telco space), etc.

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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, architects, and test results. However, this data does contain a lot of useful information. The challenge is actually spotting it. 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 in minutes and analyze in minutes, understanding where the problem is. Using test analytics can help you understand the problem and avoid it.

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That’s a very difficult question all test managers face at some point. Hopefully, by that time they know how to judge the importance of testing processes that have been carried out. But the start is just as important. You don’t want to initiate automated testing right at the wrong stage of your software’s life cycle. That’s just a loss of resources. Start with manual testing – your engineers will be able to tell when the system is stable enough and ready for automated testing.

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Whether a tester is an automation ninja or a manual tester with basic knowledge of the business flow, the tools should be agonistic to the level of the user. Ultimately these 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 expand it across multiple platforms, devices, and browsers. This ensures the right scale and coverage.

In today’s competitive world, teams need to have the ability to conduct a test anywhere, at any time. 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.


These are not the only challenges in automation testing. There are other challenges also 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.


Mallikharjun works at pCloudy as a Sr. Executive - Digital Marketing. He has 7+ years of experience in SEO, SEM, Social media and Email Marketing. He likes to read current affairs, technology blogs and enjoys Carnatic music.

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