ISTQB CT-AI
Testing AI Systems and GenAI
Fundamentals of testing AI-based systems
- What characterizes a locked AI-based system? Easy
- Which is an example of an adaptive AI-based system? Easy
- Which type of AI-based system is far easier to test? Easy
- How is an updated locked AI-based system typically treated? Easy
- Why can a single test, such as a cat classified as a dog, not reliably reflect a model's functional correctness? Easy
- What does the test oracle problem describe? Easy
- What is a proxy oracle? Easy
- Which is an example of defining output boundaries as a solution to the test oracle problem? Easy
Testing generative AI
- Which test approach is common when testing generative AI? Easy
- What is called the "input explosion problem" when testing GenAI? Easy
- What are benchmark suites used for when testing generative AI? Easy
- What is red teaming (RT)? Easy
- Why is red teaming particularly important for generative AI? Easy
- When is red teaming most effective? Easy
- What is blue teaming? Easy
Test levels and risk-based testing
- Which two specialized test levels address ML-specific risks? Easy
- Which data does input data testing consider? Easy
- To which systems should risk-based testing be applied? Easy
- Into which three areas can ML-specific risks be divided along the ML workflow? Easy
- What is ML model testing concerned with? Easy
Fundamentals of testing AI-based systems
- Where do many GenAI systems such as LLM-based chatbots stand between locked and adaptive systems? Medium
- Why can even locked AI systems with large neural networks exhibit non-deterministic behavior in practice? Medium
- How can an adaptive AI system be tested before deployment? Medium
- How can one check that the adaptations of an adaptive AI system in operation are safe? Medium
- Which reasons speak for a statistical approach to testing AI systems? Medium
- With which statistical means can a model's accuracy, fairness and robustness be quantified? Medium
- Why must a statistically significant sample of scenarios from the operational data be tested? Medium
- What causes the test oracle problem in AI systems? Medium
- Which approaches exist for the test oracle problem? Medium
- Why must testers specify environmental boundaries such as lighting, temperature or network latency? Medium
- Which limitation does consulting domain experts as a test oracle have? Medium
Testing generative AI
- What is evaluated when testing generative AI? Medium
- Which parameters besides the prompts influence the output of a GenAI system? Medium
- Which non-functional measures are relevant for GenAI systems? Medium
- Which harmful results is red teaming meant to provoke, for example? Medium
- Which steps does the typical red teaming approach comprise? Medium
- With which approaches can comprehensive coverage be achieved in red teaming? Medium
Test levels and risk-based testing
Fundamentals of testing AI-based systems
- An automotive supplier uses a fixed trained DNN for traffic sign recognition and deploys a retrained model after one year. Which statements are correct? Hard
- A team tests a locked image classification model on GPUs and in rare cases receives slightly different outputs for identical inputs. How is this to be classified? Hard
- A tester is asked to write test cases in advance for all future behaviors of an adaptive recommender system. What is there to say about this? Hard
- Why is testing adaptive AI systems before deployment more complex than testing locked systems? Hard
- A team has checked an image model with 20 test images, all classified correctly, and now wants to report "100% correct". What speaks against this? Hard
- A manufacturer of a medical AI system must demonstrate to an authority that a fairness threshold is met. Which statements are correct? Hard
- A team testing a virtual assistant cannot agree on "correct" answers because users have very different expectations. Which cause of the test oracle problem is present, and what helps? Hard
- For an image classification model there are many unlabeled test images but no expected results. Which approach fits? Hard
- A self-learning pricing system was accepted with a set of expected results. After a few weeks, many of these tests fail although the system works well. What is the reason? Hard
- A model for assessing complex protein structures delivers results that humans can hardly verify. Which statements are correct? Hard
Testing generative AI
- A team has the images of an image generator checked automatically by an image recognition system. Which statements about this are correct? Hard
- A tester receives different answers from a chatbot to the same user prompt depending on the session. Which factors are possible causes? Hard
- How is "passed" or "failed" decided when testing GenAI if the outputs are reviewed manually? Hard
- A company wants to use red teaming to check an LLM with RAG integration for security vulnerabilities before launch. Which attacks should be considered? Hard
- A healthcare chatbot is to be checked for safety using red teaming. What does this aim at, unlike security red teaming? Hard
- How does red teaming relate to benchmarks? Hard
- A team plans red teaming only for security. Which other areas can red teaming cover, and what role does regulation play? Hard
Test levels and risk-based testing
- A company uses a cloud provider's language model as a service and integrates it into its CRM. Which test levels and activities are intended for this? Hard
- A DNN was compressed for a smartphone to make it smaller. Which test level is particularly important here, and what is checked? Hard
- Which mappings of risk and area along the ML workflow are correct? Hard