Release Notes: Generative AI Version 1.0, On-prem Azure DevOps Integration

Release Notes: Generative AI Version 1.0, On-prem Azure DevOps Integration.


This week, we added a powerful and promising feature to generate test cases using AI.

Generative AI

testRigor has released the ability to add AI-based reusable rules to test cases.

  • To create an AI-based rule, simply add the specification to the test script.
  • Avoid using normal keywords so that testRigor doesn’t confuse the AI rule with a normal command.
  • Quotation marks are not necessary.
  • When the test case is triggered, a pop up will appear asking how the new command should be treated, at which time the user can select AI-based rule.
  • Once the case has been executed, AI-based rules can be modified in the Reusable Rules section by disabling the AI-based rule checkbox. Once this occurs, the rule will behave the way normal rules do.
  • As long as the AI-based rule checkbox is enabled, the specification will be executed by AI on every single execution.

*Important Note: The AI is trained to view the page as if it were the first time. It does not base its actions on any previous interaction with the UI.

See also:


We have added support for the on-premise version of Azure DevOps.


AI Applications

Certainly! Artificial Intelligence (AI) has a wide range of applications across various industries. Here are some AI applications:

1. Natural Language Processing (NLP): AI-powered chatbots, sentiment analysis, language translation, and speech recognition are all NLP applications.

2. Image Recognition: AI is used for facial recognition, object detection, and image classification in various fields such as security, healthcare, and autonomous vehicles.

3. Recommendation Systems: AI algorithms power recommendation engines in e-commerce, streaming platforms, and content curation, providing personalized suggestions to users.

4. Predictive Analytics: AI is used to predict outcomes and trends in areas such as finance, healthcare, and marketing, aiding in decision-making processes.

5. Autonomous Vehicles: AI is a critical component in the development of self-driving cars, enabling them to perceive their environment and make real-time decisions.

6. Healthcare Diagnostics: AI is used for medical image analysis, drug discovery, and predictive analytics to improve diagnostic accuracy and patient care.

These are just a few examples of the many AI applications that are transforming various industries. Each of these applications involves complex algorithms, machine learning models, and data processing techniques. If you have a specific industry or problem in mind, I can provide more detailed information about AI applications in that area.