An artificial intelligence linter applies model-based analysis to source code and can check conventions, patterns or contextual concerns beyond a traditional deterministic linter. Teams can define review logic tailored to their code and ownership boundaries.
Model-based findings are probabilistic and should be evaluated for precision, severity and developer address rate. High-confidence deterministic rules should remain in ordinary static tools when possible.
Acronyms and aliases
AI linter acronymmodel-based linter variant
General terms
Related terms
Frequently asked questions
How is an artificial intelligence linter different from a traditional linter?
A traditional linter applies fixed rules, while an artificial intelligence linter can interpret broader context but produces less deterministic findings.
When should a rule remain deterministic?
A rule should remain deterministic when it can be expressed reliably and checked cheaply without model ambiguity.
