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Exploratory AI-Infused Application Testing

Quickly learn about Exploratory AI-Infused Application Testing specifics

Zorica Micanovic avatar
Written by Zorica Micanovic
Updated over 3 months ago

Exploratory AI-Infused Application Testing is a powerful tool for freelance testers at Test IO. It allows you to:

  • leverage your creativity and

  • critical thinking skills to uncover potential issues and improve the overall performance of the AI.

This method involves testing the AI using your prompts, rather than following a predetermined set of test cases.

Key Features of Exploratory AI-Infused Application Testing

  1. Spontaneity and Flexibility: You are not bound by a script or a rigid set of instructions. You are free to interact with the system in any way you see fit, using your prompts to guide your exploration.

  2. Critical and Creative Thinking: The success of Exploratory AI-Infused Application Testing largely depends on your ability to think critically and creatively. Your deep understanding of the LLM and its potential use cases, combined with your ability to think outside the box, will enable you to identify potential issues and suggest improvements.

  3. Understanding System Behavior: Exploratory AI-Infused Application Testing is not just about finding bugs; it's also about understanding the system and its behavior. As you interact with the LLM using your prompts, you will gain a deeper understanding of how the system responds to different inputs and scenarios.

Types of Exploratory AI-Infused Application Testing and Scenarios

There are 3 Testing Types of Exploratory AI-Infused Application Testing:

  • Positive Testing is testing the AI with valid inputs and expected use cases.

  • Negative Testing is testing the AI with invalid inputs or unexpected use cases.

  • Edge Case Testing is testing the AI with extreme or boundary inputs.

Below, you can find some of the examples with Pass or Fail scenarios.

Type of Exploratory AI-Infused Application Testing

Pass Scenario

Fail Scenario

Positive Testing

If the AI is expected to translate a simple sentence from English to Spanish, providing a correct English sentence should result in an accurate Spanish translation.

If you provide a correct English sentence, but the AI translates it inaccurately or not at all.

Negative Testing

If you provide a sentence with incorrect grammar or syntax, the AI should be able to identify the error and either correct it or provide an error message.

If you provide a sentence with incorrect grammar or syntax, and the AI translates it without identifying the error.

Edge Case Testing

If you provide a very long sentence, the AI should still be able to process the input and provide a reasonable output.

If you provide a very long sentence and the AI fails to process the input or provides an incorrect output.

Exploratory AI-Infused Application Testing aims not just to find bugs, but also to understand the system's behavior and suggest improvements. When the test scenario fails, it provides valuable insights that can be used to enhance the AI's performance and usability.

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