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Area of effect

As explained in Software Testing with Generative AI

A model of the influence produced by the relationship among a person, their abilities, and the tools they use.

Area of effect models the influence produced by the relationship among a person, their abilities, and the tools they use. Testing reach grows when tools expand human abilities without replacing human direction. Human judgment alone remains limited by time, attention, and biases; tools alone lack a meaningful center unless they deliver useful feedback to people. section 1.2.2

Use the model to keep testing work balanced:

  • Identify where an LLM can extend testing ability rather than deferring the entire task to it. section 1.2.2
  • Keep a person responsible for direction and for extracting value from tool-generated feedback. section 1.2.2

File upload testing

For a secure legal-document upload feature, the acceptance criteria specify PDF, DOCX, and TXT support, a 20MB limit, progress updates, initial uploader-only access, and audit reporting. An LLM may assist with generating tests, but the tester must direct the work and judge whether the results address these criteria. section 1.2.2

Figure 1.2 An outline of how tools enhance and extend the reach of testing

Use the figure to visualize how tools enhance and extend testing reach while keeping human ability at the center. section 1.2.2

How Software Testing with Generative AI covers it

How deep it goes
Defines the human-tool relationship and illustrates it through a file-upload testing scenario.
Examples
Uses secure file uploads, acceptance criteria, generated tests, and a tool-reach diagram.
What you can do after
Apply it to identify useful LLM testing opportunities while retaining human direction and judgment.
How it connects
Connects human abilities, tools, LLMs, testing, autonomy, and feedback.

This explainer was generated by Manning's knowledge graph from the text of Software Testing with Generative AI. The section links point to the parts of the book it draws on.