Enable no-code test automation with Natural Language to web automation

Preconditions

  1. The application is live and accessible via a specific URL.
  2. The testing platform supports natural language processing and has the capability to deploy intelligent agents on the application.

Main Success Scenario

  1. Provide Application URL:
    1. The user inputs the URL of the application to be tested into the testing tool.
  2. Define Test Steps in Natural Language:
    1. The user describes the steps for various test scenarios in natural language. These steps include actions like "click on the login button," "enter credentials," "submit form," etc.
  3. Agent Activation and Test Execution:
    1. The testing tool interprets the natural language descriptions and converts them into executable commands.
    2. Intelligent agents are deployed to perform these actions on the application as specified.
  4. Collect Artifacts:
    1. As the agents execute the test scenarios, the testing tool automatically collects artifacts such as screenshots, video recordings, and system logs. These artifacts capture the state of the application at various points, documenting how the application behaves in response to the test actions.
  5. Analyze Test Outcomes:
    1. The user reviews the test outcomes, supported by the collected artifacts, to determine if the application behaves as expected under test conditions.
    2. The artifacts provide visual and data-driven insights into the application's performance and help identify any issues or anomalies.
  6. Iterative Improvement:
    1. Based on the analysis, the user may revise the natural language steps or adjust the application to address any identified issues.
    2. Additional test cycles can be initiated to validate changes and improvements.

Postconditions

  • The application has been tested thoroughly based on the defined scenarios.
  • Detailed records of the test results and artifacts are available for further review and compliance purposes.

Exception Paths

  • Misinterpretation of Natural Language Commands:
    • If the testing tool misinterprets the natural language commands, it may lead to incorrect or incomplete test actions. This requires the user to refine the language or provide more specific instructions.
  • Failure to Collect Artifacts:
    • If there is a failure in the artifact collection process, the user may lack sufficient data to fully assess the application's behavior. The user needs to rerun the test or check the tool's configuration.

Frequency of Use

  • This use case is typically executed regularly throughout the development lifecycle to ensure continuous quality assurance and to accommodate changes in the application.

Special Requirements

  • Robust network connectivity to ensure uninterrupted testing and data transfer.
  • High-performance computing resources to process natural language commands and manage simultaneous executions by agents.

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