引导式测验 · 简单 等级
AI 故障模式测验
测试根本原因分类、系统边界、误用、幂等性、匹配控制、回归案例和验证。
问题 1 的 8
A system invents a citation. Why classify this separately from a duplicated payment?
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- A system invents a citation. Why classify this separately from a duplicated payment?
- All errors should use the same mitigation
- A citation error is always a network failure
- The triggers, consequences, and useful controls differ
- The payment system cannot have model errors
- A model correctly interprets a request, but a tool acts on the wrong account. What kind of issue may this be?
- Proof the model’s language output was wrong
- Evidence the user intended the other account
- A formatting problem only
- A system-level failure outside the model’s interpretation
- Why should a retry use transaction identifiers when an action may already have completed?
- To help prevent a repeated request from duplicating the external action
- To make the model’s answer more fluent
- To eliminate authorization checks
- To ensure every retry succeeds
- How should ordinary input variability and deliberate misuse be tested?
- Only with adversarial prompts
- As distinct test categories, since they expose different weaknesses
- Only with clean standard inputs
- As identical cases requiring one metric
- A fix passes the exact failed example once. What conclusion is justified?
- That the entire failure class is eliminated
- That regression tests are no longer needed
- That this replay passed; meaningful variations and the underlying cause still need testing
- That all future inputs will behave the same
- Which control fits a tool that must not change accounts without authorization?
- A more polished response template
- A longer model context window
- A higher image resolution
- Permission limits and an explicit authorization check
- Why retain failed cases in a regression suite?
- To check whether later changes reintroduce known failures
- To guarantee the model never changes
- To replace production monitoring
- To hide system behavior from operators
- An endpoint returns HTTP 200 with stale results. What does that show?
- The request necessarily produced a useful answer
- Transport success alone does not prove task-level correctness
- The service has no operational issue
- The model’s training score must be low