5 Test planning with AI support

 

This chapter covers

  • How the value of models is associated with the use of LLMs
  • Using models with LLMs in test planning
  • Evaluating the suitability of suggestions generated by LLMs

Now that we’ve started to see how large language models (LLMs) can help support quality in development, it’s time to tackle the question of whether LLMs can generate test cases. On the surface, the answer is simple: yes, they can. But the deeper and more important question is why would you want them to generate test cases? What are we hoping to achieve by generating swathes of test cases without thought or direction? Just because we can create test cases doesn’t necessarily mean it’s the right thing to do in a given situation.

5.1 Defining test planning in modern testing

5.1.1 Test planning, LLMs, and area of effect

5.2 Focused prompts with the use of models

5.2.1 Weak prompts mean weak suggestions

5.2.2 What are models and why can they help

5.3 Combining models and LLMs to assist test planning

5.3.1 Creating a model to identify prompts

5.3.2 Experimenting with different model types

5.4 LLMs and test cases

5.4.1 Having a healthy skepticism of generated risks and test cases

Summary