testRigor AI-Based Automated Testing Tool

What is testRigor AI-Based Automated Testing Tool?

AI-based automated testing tools, like testRigor, utilize artificial intelligence to revolutionize software testing processes. These tools stand out from traditional testing platforms by integrating AI technology comprehensively into their operations. AI enables these tools to recognize various content types such as text, images, and image inscriptions within applications, facilitating more accurate testing of visual interfaces. Moreover, AI aids in autonomous test creation by analyzing websites independently and generating relevant test cases based on user interactions and site structure. This approach streamlines test creation, reduces manual effort, and enhances test coverage, ultimately leading to improved efficiency and effectiveness in software testing practices.

Who created testRigor AI-Based Automated Testing Tool?

The AI-Based Automated Testing Tool, testRigor, was created by a company that integrates AI technology comprehensively in its testing processes. It utilizes multiple Machine Learning models to enhance the efficiency of QA testing. Some key features include recognizing text, images, and image inscriptions, autonomous test creation through website analysis, detection of sudden pop-ups, classification of image types, conversion of code into executable test cases, and more. This innovative tool enables users to spend significantly less time on maintenance compared to other automation tools.

Who is testRigor AI-Based Automated Testing Tool for?

• Software Tester
• Quality Assurance Engineer
• Devops engineer
• Product Manager
• Software developer
• Business Analyst
• Project Manager
• Test Automation Engineer
• UX/UI Designer
• Technical Support Specialist

How to use testRigor AI-Based Automated Testing Tool?

Here is a step-by-step guide on how to use an AI-Based Automated Testing Tool like testRigor:

1. Recognition of Text, Images, and Image Inscriptions:

   • Utilize AI to recognize different types of content like text, images, and inscriptions within images for accurate testing of interfaces heavily relying on visual elements and text interactions.

2. Website Analysis for Autonomous Test Creation:

   • Let the tool independently analyze websites or applications to generate relevant test cases based on the site's structure, functions, and user interaction patterns automatically.

3. Identification of Sudden Pop-ups and Banners:

   • AI identifies unexpected elements like pop-ups and banners during testing, adjusting the test execution strategy on-the-fly to ensure accurate results despite disruptions.

4. Classification of Image Types:

   • AI classifies various image types within the application, enhancing understanding of the user interface and improving interaction during testing, leading to better accessibility testing.

5. Conversion of Code into Executable Test Cases:

   • Use the record-and-playback tool to convert code into human-readable and executable test cases, simplifying the test creation process for non-technical team members and ensuring robust test coverage.

6. Detection of Broken Pages:

   • Detect issues like broken pages due to missing or incorrect CSS, improving user experience by addressing issues that may be overlooked by traditional automated testing tools.

7. Building Tests Based on User Interaction Analysis:

   • Create tests based on real user interactions in live production environments to simulate actual user behavior, uncovering issues that might be missed by abstract or theoretical test cases.

By following these steps, users can leverage the AI capabilities of automated testing tools like testRigor to enhance the efficiency and effectiveness of their software testing processes.