POPL 2021 (series) / CPP 2021 (series) / Certified Programs and Proofs /
Developing and certifying Datalog optimizations in Coq/MathComp
We introduce a static analysis and two program transformations for Datalog to circumvent performance issues that arise with the implementation of primitive predicates, notably in the framework of a large scale telecommunication application. To this effect, we introduce a new trace semantics for Datalog with a verified mechanization. This work can be seen as both a first step and a proof of concept for the creation of a full-blown library of verified Datalog optimizations, on top of an existing Coq/MathComp formalization of Datalog towards the development of a realistic environment for certified data-centric applications.
Mon 18 JanDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
Mon 18 Jan
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
18:00 - 18:45 | |||
18:00 15mTalk | A Coq Formalization of Data Provenance CPP Véronique Benzaken Université Paris Saclay, Sarah Cohen-Boulakia LRI, Université de Paris Sud, CNRS (UMR8623) - Université Paris Saclay, Evelyne Contejean CNRS, Chantal Keller LRI, Univ. Paris-Sud, Rébecca Zucchini LRI, Université de Paris Sud, CNRS (UMR8623) - Université Paris Saclay Pre-print Media Attached | ||
18:15 15mTalk | Developing and certifying Datalog optimizations in Coq/MathComp CPP Pre-print Media Attached | ||
18:30 15mTalk | Machine-Checked Semantic Session TypingDistinguished Paper Award CPP Jonas Kastberg Hinrichsen IT University of Copenhagen, Daniël Louwrink University of Amsterdam, Robbert Krebbers Radboud University Nijmegen, Jesper Bengtson IT University of Copenhagen Pre-print Media Attached |