When properly implemented, automated testing can provide efficient productivity and quality improvements for product and system development projects. However, applying best practices can be a tedious task when the team is just getting started.
In this article, we aim to shed light on some of the most common challenges teams face in pursuing automation, and possibly provide valuable solutions to overcome them.
First, let’s look at the most common automated test challenges:
Select an automated method
Testers need to find appropriate test automation methods. To do this, test engineers need to find key questions and answers. For example, how to reduce the implementation and maintenance of test scripts and test suites? How do I generate useful test reports and metrics? Will automated test suites last longer?
Most of the time, answering these important questions will simplify the process of moving in the right direction. In agile development, the application under test often changes during the development cycle. Therefore, designing and implementing automated test suites to correctly identify these changes and keep systems up to date is an important maintenance effort that is both necessary and tedious. In this case, the ideal solution is to have a test automation solution that detects these problems and automatically updates and updates them.
Select the automation tool
Choosing the right automation tool is a guaranteed problem for quality assurance teams because the tool they choose does not provide 100% test coverage, or the cost of the tool exceeds the test budget. Perhaps they even lack the expertise to take full advantage of a particular tool. However, if the team doesn’t know how to use the tool, it can buy online courses for testers or hire instructors to help the team master it.
Sometimes, the tools used may not meet all requirements. In this case, start looking for solutions that cover your team’s key areas. If you find a tool that exceeds your budget, simply prepare a cost and benefit analysis and present the case to the implementation team. If the right tools are used, an analysis of bug costs can be resolved. Comparative analysis of different frameworks is key to maximizing automation ROI.
Process the data
DevOps automation leads to a lot of data that needs to be reviewed and analyzed. Teams often find themselves flying through vast amounts 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 when we try to sort the data. For example, insights from the data can help the r&d team understand what fixes need to be made. Keeping track of all the data can be a daunting task for many teams, especially those without the right tools.
To get fast feedback, you need to be able to categorize data noise. The reality of CI/CD is that it requires teams to perform tests and analyze the results in a matter of minutes to understand problems and fix them early. Using test analysis can help teams understand problems and avoid them.
Know when to start and stop testing
One of the challenges most, if not all, test managers face is when to start testing or when to stop testing. If you don’t want to start automated testing at the wrong part of the software life cycle, you need to know the answer to this question, because it can seriously impede the accurate execution of production release plans. A useful tip is to start with manual testing. Because when manual testing begins, engineers will be able to determine when the system is stable enough to be tested automatically. When the team is confident that it can push certain features or tasks for automation, it can provide a better workflow because the team understands the schedule and is ready to shut down tasks one by one and move on to the next phase.
How can these challenges be overcome?
These tools are something that all testers need to know and participate in, whether they are automated or manual testers with basic knowledge of business processes. Because in the end, manual tests with automated tools can perform automated testing tasks, while advanced testers can focus on higher-priority testing. This refers to the ability to successfully extend test automation operations. To be successful in continuous testing and automated testing, teams need to be able to see clear, accurate test results quickly and effectively. And they need to spot problems quickly. Automation generates noise, and teams need to be able to categorize it to provide the necessary evidence.
The only way to successfully solve one of the major challenges in automated testing is to use a solution that combines the above components together. If the solution is missing one of these components, a critical part of the continuous testing process is lost.
conclusion
The challenges mentioned here are not the only ones in the list of automated test challenges, though. There are many challenges to overcome on the road to successfully implementing automation. Come on, FunTester!
FunTester.Tencent Cloud Author of the Year,Boss direct hire contract author.Official GDevOps media partner, non-famous test development, welcome to follow.
- FunTester test framework architecture diagram
- Soft start of performance test
- How to become a Full stack automation engineer
- FunTester Moco Server framework architecture diagram
- Use Case Scheme of Distributed Performance Testing Framework (PART 1)
- Use Case Scheme of Distributed Performance Testing Framework (PART II)
- Appium 2.0 quick reference
- Probe into branch problems in link pressure measurement
- Agile testing is two or three things
- A complete guide to automated Testing Frameworks
- Moco framework interface hit ratio statistics practice
- Distributed performance testing framework single-node internal test