An item-score vector is a list of "scores" that a person gets on the items of a test, where "1" is correct and "0" is incorrect.
The analysis can determine how unlikely an item-score vector is compared to a hypothesized test theory model such as item response theory, or compared with the majority of item-score vectors in the sample.
Person-fit methods are used to detect item-score vectors where such external factors may be relevant, and as a result, indicate invalid measurement.
The results of the analysis might look like an examinee cheated, but the ability to prove it by returning to when the test was administered is not possible.
However, it might be useful on a larger scale; if most examinees at a certain test site or with a certain proctor have unlikely responses, an investigation might be warranted.