In repetitive and more often lengthy tests, software testing becomes time and effort-draining for the whole team instead of being a quality measure. So, there was an urgent need to speed up such processes without breaching quality and accuracy. Although automated testing made a leap in making testing processes faster, AI testing came to be […]
In repetitive and more often lengthy tests, software testing becomes time and effort-draining for the whole team instead of being a quality measure. So, there was an urgent need to speed up such processes without breaching quality and accuracy. Although automated testing made a leap in making testing processes faster, AI testing came to be game-changing! It made testing even faster, smarter, and more comprehensive, reducing time to market (TTM) and saving time and resources. So, what is AI testing and how does it enhance your testing process as a software tester?
AI Testing is the use of artificial intelligence technology in testing software. It incorporates using testing automation tools with the implementation of artificial intelligence features to accelerate it and attain more accurate testing results.
AI is no longer a surprise to affect all technological aspects, however, the point is what AI brings to the table in the world of software testing.
The core benefit of using AI in testing revolves around its significant improvement of the overall quality of the entire software testing life cycle (STLC) – in all aspects.
Here is how,
By automating the repetitive testing tasks like functional and regression testing, you have now more time to focus on other types of testing that cannot be automated and still require human intervention like exploratory tests for example. This accelerated the execution time of testing with minimal human input.
If a human does the same task repetitively, they make mistakes. If an AI tool does the same task repetitively, it learns!
One of the most important perks of implementing AI in the testing process is minimizing the error factor generated by a human doing the same task monotonously. This gives you dependable test results and detailed reports.
The benefits of AI in software testing are not limited to just making the process faster, it creates different alterations to the test scenarios and thoroughly tests the software, accordingly, predicting more in-depth and closer stimulation to the different use cases by real potential users. Which means more test comprehensiveness and more accurate reporting.
With writing test cases every day, they are more likely to be of low quality. Here, AI testing tools generate quality test cases that are dependable and reusable for future testing and be of high quality every time you use them.
Visual testing of software is one of the tests that better be automated. However, AI proved great efficiency in identifying visual defects to the smallest details like different colors, unmatched fonts, and layouts by taking screenshots, comparing different UIs, and reporting findings accurately.
This leads to:
The efficiency and accuracy of AI testing made it ideal for use at any of the testing stages. However, there is a selection of some testing types that AI testing is the best for them.
AI is now an undividable part of software testing, and it is time to add it to your software toolkit and start benefiting from it in making your work easier.
In this article, we have covered the 6 most important skills you must have to become an AI tester, and related AI testing certificates to deepen your AI testing knowledge.
We are a quality-oriented software testing company, and we promote everything that brings it, from the latest technologies to skilled software testers. With the evolution of AI in testing, we encourage you to learn more about it and expand your skills.
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