Best automation tool for automating service now application testcases

[swathi v]

Can some one please suggest best automation tool for automating service now application testcases.

1.I did a bit of research and found ATF (Automated Test Framework) tool.Did any one worked on it.If so what are the advantage/disadvantages of using that tool.

2.Did web based automation tools like cypress/selenium/RPA works for service now application testcases automation

[Utpal Dutta]

Hi Swathi,

I have worked on ATF before and it's one of the best tool to test your ServiceNow instance and maintain consistency between intances before and after any Patch/Version upgrade. Yes, the main advantage of ATF is to maintain the same consistency between instances before and after the upgrade.

You can read more about advantages and disadvantages of ATF here.

Coming to your 2nd point, yes you can use Selenium for testing ServiceNow but ATFs are better because they are integrated into the platform. However, there are few drawbacks of ATF as well but to me ATFs are better for testing ServiceNow instances.

I hope my answer helps, if it does then please mark it Helpful or Correct!

Thanks,

Utpal

[Dr Atul G- LNG]

Hi @swathi v 

every tool comes plus an minus , but if you speak from SN side, ATF is best one. But yes you cant test many thing but over all it is good.

Which you cant test

- Alignments / field placement

- Workspace changes

UI changes.

Please mark this response as correct or helpful or the solution accepted if it assisted you with your question.

Regards
Atul G.
Learn N Grow With Atul G

[YethiC]

Choosing between codeless testing and traditional automation depends on your team's skills, project complexity, and goals:

Codeless Testing:

• Ease of Use: Ideal for non-developers with intuitive drag-and-drop interfaces.
• Speed: Faster test creation and execution, suitable for rapid development cycles.
• Maintenance: AI-driven self-healing reduces maintenance efforts.

Traditional Automation:

• Flexibility: Offers more control and customization through scripting languages.
• Complex Scenarios: Better for complex, large-scale projects requiring intricate logic.
• Skill Requirements: Requires programming knowledge and a steeper learning curve.

Choose codeless testing for quick, accessible automation or traditional methods for deep customization and control.

[YethiC]

Integrating AI and Machine Learning (ML) into QA automation revolutionizes testing by enhancing efficiency and accuracy. AI algorithms analyze historical test data to identify patterns and predict potential issues, enabling smarter test case prioritization and automated test generation. ML improves defect detection by recognizing complex patterns and diagnosing root causes more effectively. Additionally, AI automation tools  can optimize test execution by dynamically adjusting strategies based on real-time data, reducing false positives and improving overall test reliability. This integration streamlines the QA process, accelerates feedback, and ensures more robust software quality.