AI can identify repeated test cases and thus remove them. Resulting efficient testing process.
It uses MI to analyze historical test data and suggest improvements to existing test scripts.
With AI, you can analyze results and get insights on potential areas of improvement.
The test scripts written through machine learning are more accurate, thus reducing errors.
It can help identify defects and bugs in the code, improving the overall quality of the software.
It can automatically generate test cases by analyzing code and identifying potential edge cases.