Certifying Standard and Stratified Datalog Inference Engines in SSReflect

International audienceWe propose a SSReflect library for logic programming in the Datalog setting. As part of this work, we give a first mechanization of standard Datalog and of its extension with stratified negation. The library contains a formalization of the model theoretical and fix-point semantics of the languages, implemented through bottom-up and, respectively, through stratified evaluation procedures. We provide corresponding soundness, termination, completeness and model minimality proofs. To this end, we rely on the Coq proof assistant and SSReflect. In this context, we also construct a preliminary framework for dealing with stratified programs. We consider this to be a necessary first step towards the certification of security-aware data-centric applications