Recognises an update anomaly in a logical data model
One fact is stored in several rows, so a change must be repeated and a partial change leaves the data contradicting itself.
Can AI do this?
AI does this well Most of the tested AI models master this. 10 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 100% | Mastered |
| gpt-6-astra | Flagship | 100% | Mastered |
| claude-fable-5-1 | Flagship | 100% | Mastered |
| gemini-3.8-flash | Mid tier | 100% | Mastered |
| gpt-6.1-sol | Mid tier | 100% | Mastered |
| claude-sonnet-5-5 | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 100% | Mastered |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: The fact stored more than once and the rows a change would have to reach
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: Account holder address held on every Account; the customer moves and three of their five accounts are updated Acceptable: Address held once on Party; Account reaches it through Account Holder
Also known as: Update anomaly (logical model)
Related knobits
Builds on
Needed for
All 56 knobits of Derive the logical data model.
Source: Review checklist 05-logical, row 2; Codd 1971; E&N 14.1.2; C&B