Challenges and solution in learning new automation tool

What are your challenges in learning new automation tool in general and how did you overcome it



Well as a consultant, I often move to different project/clients and they all use different tech. So learning a new automation tool happens quite often. I suppose it’s learning the new program language again for me.
If I have to swap programming language every ~6-12 months … I mean it in my head of course but sometimes I forget how this is done in java or python or C#.

How to overcome? Google is my best friend at that time! :slight_smile:

If it’s really about challenges of the automation tool, sometimes the lesser known tools don’t have good tutorials or guides available and then it’s just about experimenting. So I always setup a project myself and create an exercise for myself that covers most of the aspects. (assertions, oop, data driven, reporting, … )


In one way or another this question has been asked so many times, the general guidance of finding tutorials, and then starting a small self-guided project always wins out. It’s probably a even better idea if every company sets up a “guided learning” wiki with an example project idea that will allow a new joiner to the company to progress in a tool they adopted. I have seen Trello boards used for this guiding process as a way to formalize it and measure your tool mastery. It’s a great confidence builder for some people to have milestones or at least a roadmap to mastering a tool.

On the other hand, it’s more useful to divide up tools by their function so the new starter has a better idea of where a tool should generally be used. Some tools like the scripting languages are so multi-purpose , that it’s easy to get distracted, hence the need for teams to guide new joiners. Talking to your team is key to making sure you are learning with the right “outcomes” in mind. There will always be many tools.


Are you learning any tool at the moment? If yes, then which tool and what are the problems you are facing?

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For your product pipeline and system development projects, Automation testing services can be a highly effective productivity booster and quality enhancer if it is implemented correctly. In this article, I will provide you some of the most common challenges that teams face as they pursue automation and possibly provide valuable solutions to overcome these challenges.

Let’s have a look at the most prevalent automation testing challenges along with their solutions:

1. Selecting a suitable automation testing approach:

  • Testers of automation testing services need to find an appropriate test automation approach. They should know 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? 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.

Solution: 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.

2. The Lack of Necessary Skills:

  • Although automation testing services offers teams a number of benefits, not everyone has the right skills to do it successfully. Because of this, manual testing still occurs as teams compensate for any existing automation gaps. Or, they see it as a stable alternative.
    This results in delays and a disconnect with the R&D team.

Solution: Either hire the right skill-set to execute on automated tests or train your team to do it the right way.

3. 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.

Solution: 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

4. Rigorous lab management:

- 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.

Solution: 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.

5. Teams Don’t Stabilize Tests Before Automating:

  • DevOps teams building all their tests and running them together without stabilizing first. The result is failure, frustration, and trust issues with automation. Because of this, teams of automation testing services revert back to manual testing.

Solution: The best practice for building a test automation foundation is this modular execution approach:

  • Build your test locally over a real device/browser.
  • Run your test daily to ensure a balanced execution and that there are no blockers.
  • Tie your execution to CI and run your test constantly (at least nightly).
  • Increase your digital platform test coverage and execute more frequently.
  • Maximize your automation coverage up to 90% (to get into the DevOps-friendly zone).

6. 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.

Solution: 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.

7. 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.

Solution: 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.

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It depend, if using any paid tool that you will also get support and can help in learn and proceed to automate

if open source then required lots of learning , Hands-On, read blogs etc

Any specific automaton tool you looking for?

Here we will look into the challenges in Test Automation and how to overcome them.
Top challenges in Test Automation
1.Selecting and using the right tool
2.Identifying a starting strategy
3.Selecting a proper testing approach
4.High upfront investment cost
Overcoming these challenges include,
1.The tools should be understandable
2.Teams need to have the ability to conduct a test anywhere, anytime
3.Team need to be able to see clear and accurate test results quickly
4.Ensure the required scaling and test coverage

Is this list in order with a specific context? Because I’m seem different kinds of challenge in your list which impact differently for legacy/web/mobile/services products. Jeffrey was really asking a “how do I learn” question though.