2.1.1. Checker view

Considering a constraint for which all variables are fixed, the checker view is about finding an algorithm that checks whether a ground instance of that constraint holds or not. In the context of learning models, the usage of dedicated checkers rather than general filtering algorithms is crucial for performance issues.

For the $\mathrm{𝚊𝚕𝚕𝚍𝚒𝚏𝚏𝚎𝚛𝚎𝚗𝚝}$$\left(〈{x}_{1},{x}_{2},\cdots ,{x}_{n}〉\right)$ constraint one can first sort the sequence ${x}_{1},{x}_{2},\cdots ,{x}_{n}$ and then check that adjacent values are distinct, or alternatively, insert each value into a hash table in order to check that no value occurs more than once.